Difference between revisions of "Goherr: Fish consumption study"

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Question

How Baltic herring and salmon are used as human food in Baltic sea countries? Which determinants affect on people’s eating habits of these fish species?

Answer

Original questionnaire analysis results

13.3.2017 --# : These should be presented somewhere --Arja (talk) 07:39, 26 April 2017 (UTC)

Consumption amount estimates

Model run 21.4.2017 [1] first distribution
Model run 18.5.2017 with modelled data; with direct survey data

+ Show code - Hide code

# This is code Op_en7749/ on page [[Goherr: Fish consumption study#Answer]]

library(OpasnetUtils)
library(ggplot2)

objects.latest("Op_en7749", code_name="initiate") # [[Goherr: Fish consumption study]] ovariables

if(usesurvey) {
  objects.latest("Op_en7749", code_name="surveyjsp") # jsp ovariable directly based on survey data (N=2217)
  openv.setN(nrow(jsp@data))
}

amount <- EvalOutput(amount)

if(usesurvey) {
  oprint(summary(amount, marginals=c("Gender", "Country", "Fish","Ages")))
  
  print(ggplot(amount@output, aes(x=amountResult+0.1, colour=Country))+stat_ecdf()+scale_x_log10()+facet_wrap(~ Fish)+
    labs(x="Fish consumption (g /d)", y="Cumulative frequency")+theme_gray(base_size=24))
  print(ggplot(amount@output, aes(x=amountResult+0.1, colour=Ages))+stat_ecdf()+scale_x_log10()+facet_grid(Country ~ Fish)+
    labs(x="Fish consumption (g /d)", y="Cumulative frequency")+theme_gray(base_size=24))
  print(ggplot(amount@output, aes(x=amountResult+0.1, colour=Gender))+stat_ecdf()+scale_x_log10()+facet_grid(Country ~ Fish)+
    labs(x="Fish consumption (g /d)", y="Cumulative frequency")+theme_gray(base_size=24))
  
  print(ggplot(often@output, aes(x=oftenResult+0.1, colour=Country))+stat_ecdf()+scale_x_log10()+facet_wrap(~ Fish))
  print(ggplot(oftenside@output, aes(x=oftensideResult+0.1, colour=Country))+stat_ecdf()+scale_x_log10()+facet_wrap(~ Fish))
  print(ggplot(much@output, aes(x=muchResult+0.1, colour=Country))+stat_ecdf()+scale_x_log10()+facet_wrap(~ Fish))
  print(ggplot(muchside@output, aes(x=muchsideResult+0.1, colour=Country))+stat_ecdf()+scale_x_log10()+facet_wrap(~ Fish))
  
} else {
  oprint(summary(amount, marginals=c("Fish")))
  
  print(ggplot(amount@output, aes(x=amountResult+0.1, colour=Fish))+stat_ecdf()+scale_x_log10()+
    labs(x="Fish consumption (g /d)", y="Cumulative frequency")+theme_gray(base_size=24))
  
  print(ggplot(often@output, aes(x=oftenResult+0.1, colour=Fish))+stat_ecdf()+scale_x_log10())
  print(ggplot(oftenside@output, aes(x=oftensideResult+0.1, colour=Fish))+stat_ecdf()+scale_x_log10())
  print(ggplot(much@output, aes(x=muchResult+0.1, colour=Fish))+stat_ecdf()+scale_x_log10())
  print(ggplot(muchside@output, aes(x=muchsideResult+0.1, colour=Fish))+stat_ecdf()+scale_x_log10())
}

Rationale

Survey of eating habits of Baltic herring and salmon in Denmark, Estonia, Finland and Sweden has been done in September 2016 by Taloustutkimus oy. Content of the questionnaire can be accessed in Google drive. The actual data can be found from the link below (see Data).

Data

Questionnaire

Original datafile File:Goherr fish consumption.csv.

Show details

Questions in the Goherr questionnaire(-)
Obs	Index	Full question	Question
1	V1	Country	Country
2	V2	1. What is the postal code of your residence?	Postal code
3	V3	2. What is your gender?	Gender
4	V4	2. How old are you?	Age
5	V5	3. What is the level of your highest education?	Education
6	V6	4. How would you rate the purchasing power of your household?	Purchasing power
7	V7	5. Which of the following food supplements (as a separate product or as a part of some multicompound) do you eat often at least part of the year?:Fatty acids (Omega 3, DHA, EPA etc.)	Omega3
8	V8	5. Which of the following food supplements (as a separate product or as a part of some multicompound) do you eat often at least part of the year?:D vitamin	Vitamin D
9	V9	5. Which of the following food supplements (as a separate product or as a part of some multicompound) do you eat often at least part of the year?:Other vitamins	Other vitamins
10	V10	5. Which of the following food supplements (as a separate product or as a part of some multicompound) do you eat often at least part of the year?:None of the above	No vitamins
11	V11	5. Which of the following food supplements (as a separate product or as a part of some multicompound) do you eat often at least part of the year?:Don't Know	Unknown vitamins
12	V12	6. Does someone in your household fish?:No	No fishing
13	V13	6. Does someone in your household fish?:Yes, for recreational purposes	Recreational
14	V14	6. Does someone in your household fish?:Yes, for household use	Household use
15	V15	6. Does someone in your household fish?:Yes, as a professional fisherman	Professional fishing
16	V16	7. Do you eat fish?	Eat fish
17	V17	8. Why don't you eat fish?:Allergy	Allergy
18	V18	8. Why don't you eat fish?:I don't like the taste	Bad taste
19	V19	8. Why don't you eat fish?:I don't like fish bones	Bones
20	V20	8. Why don't you eat fish?:Difficult to cook	Cooking difficult
21	V21	8. Why don't you eat fish?Health risks	Health risks fish
22	V22	8. Why don't you eat fish?:I'm not used to	Not used to
23	V23	8. Why don't you eat fish?:I'm concerned about the sustainability of fish stocks	Sustainability fish
24	V24	8. Why don't you eat fish?:It is ethically wrong to eat animals	Ethically wrong
25	V25	8. Why don't you eat fish?:I'm a vegetarian	Vegetarian
26	V26	8. Why don't you eat fish?:Don't Know	Why not fish unknown
27	V27	8. Why don't you eat fish?:Other	Why not fish other
28	V28	8. Why don't you eat fish?:Other open	Why not fish open
29	V29	9. How often do you eat fish?	How often fish
30	V30	10. Do you eat salmon or trout at least sometimes?	Eat salmon
31	V31	11. Which of the following salmonids do you eat at least sometimes?:Wild Baltic salmon	Baltic salmon
32	V32	11. Which of the following salmonids do you eat at least sometimes?:Wild Atlantic salmon	Atlantic salmon
33	V33	11. Which of the following salmonids do you eat at least sometimes?:Norwegian cultured salmon	Norwegian salmon
34	V34	11. Which of the following salmonids do you eat at least sometimes?:Rainbow trout	Rainbow trout
35	V35	11. Which of the following salmonids do you eat at least sometimes?:I never know which salmon I eat	Unknown salmon
36	V36	11. Which of the following salmonids do you eat at least sometimes?:Some other salmon, what?	Other salmon
37	V37	11. Which of the following salmonids do you eat at least sometimes?:Other open	Salmon open
38	V38	12. Where do you usually get the wild Baltic salmon that you eat?:Someone in our hosehold catches it	Own catch BS
39	V39	12. Where do you usually get the wild Baltic salmon that you eat?:Buy from a grocery store	Grocery store BS
40	V40	12. Where do you usually get the wild Baltic salmon that you eat?:Buy from a market place/fishmonger or similar	Market place BS
41	V41	12. Where do you usually get the wild Baltic salmon that you eat?:Eat in a restaurant/cafe/canteen or similar	Restaurant BS
42	V42	12. Where do you usually get the wild Baltic salmon that you eat?:Directly from a fisher	Fisher BS
43	V43	12. Where do you usually get the wild Baltic salmon that you eat?:From a relative, friend, or similar	Friend BS
44	V44	12. Where do you usually get the wild Baltic salmon that you eat?:Other	Where BS other
45	V45	12. Where do you usually get the wild Baltic salmon that you eat?:Other open	Where BS open
46	V46	13. How often do you on average eat wild Baltic salmon as an ingredient in a dish (i.e. as part of a soup, gravy, sushi, casserole etc.)?	How often BS
47	V47	14. How much on average do you eat of a dish with wild Baltic salmon in it? Think of a medium sized lunch plate and the amount of the whole dish, not just the salmon.	How much BS
48	V48	15. How often do you on average eat wild Baltic salmon as a side dish (i.e as a separate product such as fish balls, stake, fillets, graved, canned etc.)?	How often side BS
49	V49	16. What is the average amount of wild Baltic salmon as a side dish? Think of a medium sized lunch plate.	How much side BS
50	V50	17. Select up to three most important reasons for you to eat wild Baltic salmon?:It tastes good	Tastes good BS
51	V51	17. Select up to three most important reasons for you to eat wild Baltic salmon?:I caught it	Self caught BS
52	V52	17. Select up to three most important reasons for you to eat wild Baltic salmon?:It's easy to cook	Easy to cook BS
53	V53	17. Select up to three most important reasons for you to eat wild Baltic salmon?:It's quick to cook	Quick to cook BS
54	V54	17. Select up to three most important reasons for you to eat wild Baltic salmon?:It's readily available	Readily available BS
55	V55	17. Select up to three most important reasons for you to eat wild Baltic salmon?:It's healthy	Healthy BS
56	V56	17. Select up to three most important reasons for you to eat wild Baltic salmon?:It's inexpensive	Inexpensive BS
57	V57	17. Select up to three most important reasons for you to eat wild Baltic salmon?:My family likes it	Family likes it BS
58	V58	17. Select up to three most important reasons for you to eat wild Baltic salmon?:It's environmentally/climate friendly choice	Environmental BS
59	V59	17. Select up to three most important reasons for you to eat wild Baltic salmon?:It's a traditional dish	Traditional BS
60	V60	17. Select up to three most important reasons for you to eat wild Baltic salmon?:Some other reasons, what?	Why BS other
61	V61	17. Select up to three most important reasons for you to eat wild Baltic salmon?:Other open	Why BS open
62	V62	18. You answered in the previous question that you don't eat wild Baltic salmon. Select up to three most important reasons for why not eating it.:I don't like the taste	Bad taste BS
63	V63	18. You answered in the previous question that you don't eat wild Baltic salmon. Select up to three most important reasons for why not eating it.:I am not used to eating it / not offered at home	Not used to BS
64	V64	18. You answered in the previous question that you don't eat wild Baltic salmon. Select up to three most important reasons for why not eating it.:I don't know how to cook it	Cannot cook BS
65	V65	18. You answered in the previous question that you don't eat wild Baltic salmon. Select up to three most important reasons for why not eating it.:It is not easily available	Not available BS
66	V66	18. You answered in the previous question that you don't eat wild Baltic salmon. Select up to three most important reasons for why not eating it.:I'm worried about the possible health risks caused by the harmful chemicals in it	Health risks BS
67	V67	18. You answered in the previous question that you don't eat wild Baltic salmon. Select up to three most important reasons for why not eating it.:I doubt the quality/freshness of the products	Quality issues BS
68	V68	18. You answered in the previous question that you don't eat wild Baltic salmon. Select up to three most important reasons for why not eating it.:I'm worried about the sustainability of the stocks	Sustainability BS
69	V69	18. You answered in the previous question that you don't eat wild Baltic salmon. Select up to three most important reasons for why not eating it.:It doesn't belong to traditional dishes of my home area	Not traditional BS
70	V70	18. You answered in the previous question that you don't eat wild Baltic salmon. Select up to three most important reasons for why not eating it.:It is too expensive	Expensive BS
71	V71	18. You answered in the previous question that you don't eat wild Baltic salmon. Select up to three most important reasons for why not eating it.:Some other reason, what?	Why not BS other
72	V72	18. You answered in the previous question that you don't eat wild Baltic salmon. Select up to three most important reasons for why not eating it.:Other open	Why not BS open
73	V73	19. How would the following factors influence on your consumption of wild Baltic salmon compared to your current use? Select one for each option:Lower price	Lower price BS
74	V74	19. How would the following factors influence on your consumption of wild Baltic salmon compared to your current use? Select one for each option:Higher price	Higher price BS
75	V75	19. How would the following factors influence on your consumption of wild Baltic salmon compared to your current use? Select one for each option:Better availability	Better availability BS
76	V76	19. How would the following factors influence on your consumption of wild Baltic salmon compared to your current use? Select one for each option:Availability of wider variety of ready meals / refined products	Ready meals BS
77	V77	19. How would the following factors influence on your consumption of wild Baltic salmon compared to your current use? Select one for each option:Cooking suggestions and recipes provided within the store or in the package.	Recipes BS
78	V78	19. How would the following factors influence on your consumption of wild Baltic salmon compared to your current use? Select one for each option:Better information (e.g. package markings or in the store) on the catch date, area, fisher and/or the refiner	Package markings BS
79	V79	19. How would the following factors influence on your consumption of wild Baltic salmon compared to your current use? Select one for each option:Improvement of the stocks (eco-labelling)	Eco labelling BS
80	V80	19. How would the following factors influence on your consumption of wild Baltic salmon compared to your current use? Select one for each option:Lower level of harmful chemicals in the fish	Less chemicals BS
81	V81	19. How would the following factors influence on your consumption of wild Baltic salmon compared to your current use? Select one for each option:National food safety authorities publish a recommendation to eat it	Recommended BS
82	V82	19. How would the following factors influence on your consumption of wild Baltic salmon compared to your current use? Select one for each option:National food safety authorities publish a recommendation to limit eating it	Not recommended BS
83	V83	19. How would the following factors influence on your consumption of wild Baltic salmon compared to your current use? Select one for each option:Some other reason, what?	Change BS other
84	V84	19. How would the following factors influence on your consumption of wild Baltic salmon compared to your current use? Select one for each option:Other open	Change BS open
85	V85	20. Do you eat any herring (Baltic or other) at least sometimes?	Eat herring
86	V86	21. Do you eat Baltic herring? This means herring caught from Baltic sea, not from Atlantic ocean	Eat BH
87	V87	22. Where do you usually get the wild Baltic herring that you eat?:Someone in our hosehold catches it	Own catch BH
88	V88	22. Where do you usually get the wild Baltic herring that you eat?:Buy from a grocery store	Grocery store BH
89	V89	22. Where do you usually get the wild Baltic herring that you eat?:Buy from a market place/fishmonger or similar	Market place BH
90	V90	22. Where do you usually get the wild Baltic herring that you eat?:Eat in a restaurant/cafe/canteen or similar	Restaurant BH
91	V91	22. Where do you usually get the wild Baltic herring that you eat?:Directly from a fisher	Fisher BH
92	V92	22. Where do you usually get the wild Baltic herring that you eat?:From a relative, friend, or similar	Friend BH
93	V93	22. Where do you usually get the wild Baltic herring that you eat?:Other	Where BH other
94	V94	22. Where do you usually get the wild Baltic herring that you eat?:Other open	Where BH open
95	V95	23. How often do you on average eat Baltic herring as ingredient of a dish? (i.e as part of a dish such as in a casserole or some other food including Baltic herring)?	How often BH
96	V96	24. How much on average do you eat of a dish with Baltic herring in it? Think of a medium sized lunch plate and the amount of the whole dish, not just the amount of Baltic herring	How much BH
97	V97	25. How often do you on average eat whole Baltic herrings or fillets as a side dish (fried, smoked, rolls, pickled, salted or otherwise prepared)?	How often side BH
98	V98	26. How much on average of Baltic herring as a side dish (think of a regular sized lunch plate)?	How much side BH
99	V99	27. Select up to three most important reasons for you to eat Baltic herring?:It tastes good	Tastes good BH
100	V100	27. Select up to three most important reasons for you to eat Baltic herring?:I caught it	Self caught BH
101	V101	27. Select up to three most important reasons for you to eat Baltic herring?:It's easy to cook	Easy to cook BH
102	V102	27. Select up to three most important reasons for you to eat Baltic herring?:It's quick to cook	Quick to cook BH
103	V103	27. Select up to three most important reasons for you to eat Baltic herring?:It's readily available	Readily available BH
104	V104	27. Select up to three most important reasons for you to eat Baltic herring?:It's healthy	Healthy BH
105	V105	27. Select up to three most important reasons for you to eat Baltic herring?:It's inexpensive	Inexpensive BH
106	V106	27. Select up to three most important reasons for you to eat Baltic herring?:My family likes it	Family likes it BH
107	V107	27. Select up to three most important reasons for you to eat Baltic herring?:It's environmentally/climate friendly choice	Environmental BH
108	V108	27. Select up to three most important reasons for you to eat Baltic herring?:It's a traditional dish	Traditional BH
109	V109	27. Select up to three most important reasons for you to eat Baltic herring?:Some other reasons, what?	Why BH other
110	V110	27. Select up to three most important reasons for you to eat Baltic herring?:Other open	Why BH open
111	V111	28. You answered in the previous question that you don't eat Baltic herring. Select up to three most important reasons for why not eating it.:I don't like the taste and/or smell of it	Bad taste BH
112	V112	28. You answered in the previous question that you don't eat Baltic herring. Select up to three most important reasons for why not eating it.:I am not used to eating it / not offered at home	Not used to BH
113	V113	28. You answered in the previous question that you don't eat Baltic herring. Select up to three most important reasons for why not eating it.:I don't know how to cook it	Cannot cook BH
114	V114	28. You answered in the previous question that you don't eat Baltic herring. Select up to three most important reasons for why not eating it.:It is difficult to cook	Difficult to cook BH
115	V115	28. You answered in the previous question that you don't eat Baltic herring. Select up to three most important reasons for why not eating it.:It is not easily available	Not available BH
116	V116	28. You answered in the previous question that you don't eat Baltic herring. Select up to three most important reasons for why not eating it.:I'm worried about the possible risks caused by the harmful chemicals in it	Health risks BH
117	V117	28. You answered in the previous question that you don't eat Baltic herring. Select up to three most important reasons for why not eating it.:It is more suitable for animal feed than human food	Better for feed BH
118	V118	28. You answered in the previous question that you don't eat Baltic herring. Select up to three most important reasons for why not eating it.:I doubt the quality/freshness of the products	Quality issues BH
119	V119	28. You answered in the previous question that you don't eat Baltic herring. Select up to three most important reasons for why not eating it.:I'm worried about the sustainability of the stocks	Sustainability BH
120	V120	28. You answered in the previous question that you don't eat Baltic herring. Select up to three most important reasons for why not eating it.:It doesn't belong to traditional dishes of my home area	Not traditional BH
121	V121	28. You answered in the previous question that you don't eat Baltic herring. Select up to three most important reasons for why not eating it.:Some other reason, what?	Why not BH other
122	V122	28. You answered in the previous question that you don't eat Baltic herring. Select up to three most important reasons for why not eating it.:Other open	Why not BH open
123	V123	29. How would the following factors influence your consumption of Baltic herring compared to your current use? Select one option for each row.:Lower price	Lower price BH
124	V124	29. How would the following factors influence your consumption of Baltic herring compared to your current use? Select one option for each row.:Higher price	Higher price BH
125	V125	29. How would the following factors influence your consumption of Baltic herring compared to your current use? Select one option for each row.:Better availability	Better availability BH
126	V126	29. How would the following factors influence your consumption of Baltic herring compared to your current use? Select one option for each row.:Availability of wider variety of ready meals / processed products	Ready meals BH
127	V127	29. How would the following factors influence your consumption of Baltic herring compared to your current use? Select one option for each row.:Cooking suggestions and recipes provided in the store or in the package.	Recipes BH
128	V128	29. How would the following factors influence your consumption of Baltic herring compared to your current use? Select one option for each row.:Better information (e.g. package markings or in the store) on the catch date, area, fisher and/or processing company.	Package markings BH
129	V129	29. How would the following factors influence your consumption of Baltic herring compared to your current use? Select one option for each row.:Improved stocks (eco-labelling)	Eco labelling BH
130	V130	29. How would the following factors influence your consumption of Baltic herring compared to your current use? Select one option for each row.:Lower level of harmful chemicals in the fish	Less chemicals BH
131	V131	29. How would the following factors influence your consumption of Baltic herring compared to your current use? Select one option for each row.:National food safety authorities publish a recommendation to eat it	Recommended BH
132	V132	29. How would the following factors influence your consumption of Baltic herring compared to your current use? Select one option for each row.:National food safety authorities publish a recommendation to limit eating it	Not recommended BH
133	V133	29. How would the following factors influence your consumption of Baltic herring compared to your current use? Select one option for each row.:Some other reason, what?	Change BH other
134	V134	29. How would the following factors influence your consumption of Baltic herring compared to your current use? Select one option for each row.:Other open	Change BH open
135	V135	30. Are you familiar with the possible eating recommendations of Baltic herring and/or wild Baltic salmon in your country?	Recommendation awareness
136	V136	31. How strongly do you agree or disagree with the following statements on Baltic salmon? Please indicate your position by selecting a number from -5 (strongly disagree) to 5 (strongly agree).:It contributes to the economic wellbeing of the society	Economic wellbeing BS
137	V137	31. How strongly do you agree or disagree with the following statements on Baltic salmon? Please indicate your position by selecting a number from -5 (strongly disagree) to 5 (strongly agree).:It is a natural resource for humans to utilize	Natural resource BS
138	V138	31. How strongly do you agree or disagree with the following statements on Baltic salmon? Please indicate your position by selecting a number from -5 (strongly disagree) to 5 (strongly agree).:It belongs to all Baltic Sea citizens equally	Belongs to all BS
139	V139	31. How strongly do you agree or disagree with the following statements on Baltic salmon? Please indicate your position by selecting a number from -5 (strongly disagree) to 5 (strongly agree).:It involves long traditions related to fishing and fish eating	Long traditions BS
140	V140	31. How strongly do you agree or disagree with the following statements on Baltic salmon? Please indicate your position by selecting a number from -5 (strongly disagree) to 5 (strongly agree).:It inspires to search experiences from nature, cultural sites, fish markets or from different dishes	Inspiring experiences BS
141	V141	31. How strongly do you agree or disagree with the following statements on Baltic salmon? Please indicate your position by selecting a number from -5 (strongly disagree) to 5 (strongly agree).:It is among the most renowned fish species of the Baltic Sea	Renowned species BS
142	V142	31. How strongly do you agree or disagree with the following statements on Baltic salmon? Please indicate your position by selecting a number from -5 (strongly disagree) to 5 (strongly agree).:It is part of the Baltic Sea ecosystem	Part of ecosystem BS
143	V143	31. How strongly do you agree or disagree with the following statements on Baltic salmon? Please indicate your position by selecting a number from -5 (strongly disagree) to 5 (strongly agree).:I have an emotional bond to it	Emotional bond BS
144	V144	31. How strongly do you agree or disagree with the following statements on Baltic salmon? Please indicate your position by selecting a number from -5 (strongly disagree) to 5 (strongly agree).:It helps me to achieve my personal aims	Personal aims
145	V145	32. How strongly do you agree or disagree with the following statements on Baltic herring? Please indicate your position by selecting a number from -5 (strongly disagree) to 5 (strongly agree).:It contributes to the economic wellbeing of the society	Economic wellbeing BH
146	V146	32. How strongly do you agree or disagree with the following statements on Baltic herring? Please indicate your position by selecting a number from -5 (strongly disagree) to 5 (strongly agree).:It is a natural resource for humans to utilize	Natural resource BH
147	V147	32. How strongly do you agree or disagree with the following statements on Baltic herring? Please indicate your position by selecting a number from -5 (strongly disagree) to 5 (strongly agree).:It belongs to all Baltic Sea citizens equally	Belongs to all BH
148	V148	32. How strongly do you agree or disagree with the following statements on Baltic herring? Please indicate your position by selecting a number from -5 (strongly disagree) to 5 (strongly agree).:It involves long traditions related to fishing and fish eating	Long traditions BH
149	V149	32. How strongly do you agree or disagree with the following statements on Baltic herring? Please indicate your position by selecting a number from -5 (strongly disagree) to 5 (strongly agree).:It inspires to search experiences from nature, cultural sites, fish markets or from different dishes	Inspiring experiences BH
150	V150	32. How strongly do you agree or disagree with the following statements on Baltic herring? Please indicate your position by selecting a number from -5 (strongly disagree) to 5 (strongly agree).:It is among the most renowned fish species of the Baltic Sea	Renowned species BH
151	V151	32. How strongly do you agree or disagree with the following statements on Baltic herring? Please indicate your position by selecting a number from -5 (strongly disagree) to 5 (strongly agree).:It is part of the Baltic Sea ecosystem	Part of ecosystem BH
152	V152	32. How strongly do you agree or disagree with the following statements on Baltic herring? Please indicate your position by selecting a number from -5 (strongly disagree) to 5 (strongly agree).:I have an emotional bond to it	Emotional bond BH
153	V153	32. How strongly do you agree or disagree with the following statements on Baltic herring? Please indicate your position by selecting a number from -5 (strongly disagree) to 5 (strongly agree).:It helps me to achieve my personal aims	Personal aims BH
154	V154	Weighting	Weighting
155	V155	How old are you? Age category FI	Age category FI
156	V156	2. How old are you? Age category SWE, DK, EST	Age category other
157	V157	Row number of respondent	Row
158	V158	Age category "18-45" or ">45"	Ages

Assumptions

The following assumptions are used:

Assumptions for calculations(-)
Obs	Variable	Value	Unit	Result	Description
1	freq	1	times /a	0	Never
2	freq	2	times /a	0.5 - 0.9	less than once a year
3	freq	3	times /a	2 - 5	A few times a year
4	freq	4	times /a	12 - 36	1 - 3 times per month
5	freq	5	times /a	52	once a week
6	freq	6	times /a	104 - 208	2 - 4 times per week
7	freq	7	times /a	260 - 364	5 or more times per week
8	amdish	1	g /serving	20 - 70	1/6 plate or below (50 grams)
9	amdish	2	g /serving	70 - 130	1/3 plate (100 grams)
10	amdish	3	g /serving	120 - 180	1/2 plate (150 grams)
11	amdish	4	g /serving	170 - 230	2/3 plate (200 grams)
12	amdish	5	g /serving	220 - 280	5/6 plate (250 grams)
13	amdish	6	g /serving	270 - 400	full plate (300 grams)
14	amdish	7	g /serving	400 - 550	overly full plate (500 grams)
15	ingredient		fraction	0.1 - 0.3	Fraction of fish in the dish
16	amside	1	g /serving	20 - 70	1/6 plate or below (50 grams)
17	amside	2	g /serving	70 - 130	1/4 plate (100 grams)
18	amside	3	g /serving	120 - 180	1/2 plate (150 grams)
19	amside	4	g /serving	170 - 230	2/3 plate (200 grams)
20	amside	5	g /serving	220 - 280	5/6 plate (250 grams)

Preprocessing

This code is used to preprocess the original questionnaire data from the above .csv file and to store the data as a usable variable to Opasnet base. The code stores a data.frame named survey.

Model run 13.4.2017 [2]
Model run 20.4.2017 [3] (contains surv and helping vectors)
Model run 21.4.2017 [4] surv contains Eatfish, Eatherr and Eatsalm as columns.

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# This code is Op_en7749/preprocess2 on page [[Goherr: Fish consumption study]]

library(OpasnetUtils)

objects.latest("Op_en6007", code_name = "answer") # [[OpasnetUtils/Drafts]] webropol.convert, merge.questions

############# Data preprocessing

# Get the data either from Opasnet or your own hard drive.

#Survey original file: N:/Ymal/Projects/Goherr/WP5/Goherr_fish_consumption.csv

survey <- opasnet.csv(
  "5/57/Goherr_fish_consumption.csv", 
  wiki = "opasnet_en", sep = ";", fill = TRUE, quote = "\""
)
#survey <- re#ad.csv(file = "N:/Ymal/Projects/Goherr/WP5/Goherr_fish_consumption.csv",
#                   header=FALSE, sep=";", fill = TRUE, quote="\"")

# Data file is converted to data.frame using levels at row 2121.
survey <- webropol.convert(survey, 2121, textmark = ":Other open") 

# Take the relevant columnames from the table on the page.
colnames(survey) <- gsub(" ",  ".",
  opbase.data("Op_en7749", subset = "Questions in the Goherr questionnaire")$Result[1:ncol(survey)]
)
survey$Row <- 1:nrow(survey)
survey$Weighting <- as.double(gsub(",",".", survey$Weighting))
survey$Ages <- factor(
  ifelse(as.numeric(as.character(survey$Age)) < 46, "18-45",">45"),
  levels = c("18-45", ">45"), ordered = TRUE
)

# webropol.convert should put these in the right order but doesn't. So do it manually.

freqlist <- c(
  "less than once a year",
  "A few times a year",
  "1 - 3 times per month",
  "once a week",
  "2 - 4 times per week",
  "5 or more times per week"
)

amlist <- c(
  "1/6 plate or below (50 grams)",
  "1/3 plate (100 grams)",
  "1/2 plate (150 grams)",
  "2/3 plate (200 grams)",
  "5/6 plate (250 grams)",
  "full plate (300 grams)",
  "overly full plate (500 grams)"
  #  "Not able to estimate"
)

sidel <- c(
  "1/6 plate or below (50 grams)",
  "1/4 plate (100 grams)",
  "1/2 plate (150 grams)",
  "2/3 plate (200 grams)",
  "5/6 plate (250 grams)"
  #  "Not able to estimate"
)

fishamounts <- c(29,46:49,95:98)
colnames(survey)[fishamounts]
#[1] "How.often.fish"    "How.often.BS"      "How.much.BS"       "How.often.side.BS"
#[5] "How.much.side.BS"  "How.often.BH"      "How.much.BH"       "How.often.side.BH"
#[9] "How.much.side.BH" 

ansl <- list(
  freqlist,
  c("Never", freqlist),
  amlist,
  c("Never", freqlist),
  sidel,
  c("Never", freqlist),
  amlist,
  c("Never", freqlist),
  sidel
)

for (i in 1:length(fishamounts)) {
  survey[[fishamounts[i]]] <- factor(survey[[fishamounts[i]]], levels = ansl[[i]], ordered = TRUE)
}

oprint(head(survey))

agel <- as.character(unique(survey$Ages))
countryl <- sort(as.character(unique(survey$Country)))
genderl <- sort(as.character(unique(survey$Gender)))
fisl <- c("Salmon", "Herring")

# Interesting fish eating questions
surv <- survey[c(1,3,158,16,29,30,31,46:49,86,95:98)]
colnames(surv)
#[1] "Country"                       "Gender"                       
#[3] "Ages"                          "Fish eating"                  
#[5] "How often eat fish"            "Salmon eating"                
#[7] "Baltic salmon"                 "How often Baltic salmon"      
#[9] "How much Baltic salmon"        "How often side Baltic salmon" 
#[11] "How much side Baltic salmon"   "Eat Baltic herring"           
#[13] "How often Baltic herring"      "How much Baltic herring"      
#[15] "How often side Baltic herring" "How much side Baltic herring" 

# For estimating distributions, we should 
#1 remove people with Fish eating = No (142)
#2 merge Eat Baltic herring = I don't know with No (How often BH = NA always)
#3 merge Baltic salmon = NA with No (because they usually have answered BH questions)

oprint(table(is.na(rowSums(sapply(surv[4:16], as.numeric)))))
# BUT: there are so many missing values, that we just model BH and BS separately now.

surv <- as.data.frame(lapply(surv, FUN = function(x) as.integer(x))) # Coerce to integers
surv[is.na(surv[[12]]) | surv[[12]] == 3 , 12] <- 1 # Eat Baltic herring: I don't know --> No

# Row numbers for respondents that have eaten fish, Baltic salmon, and Baltic herring
surv$Eatfish <- surv[[4]] %in% 2
surv$Eatsalm <- surv[[7]] %in% 2 & !is.na(rowSums(surv[7:11]))
surv$Eatherr <- surv[[12]] %in% 2 & !is.na(rowSums(surv[13:16]))

oprint(table(surv[c("Eatsalm", "Eatherr", "Eatfish")], useNA = "ifany"))

# Oletetaan, että covarianssimatriisi on vakio kaikille maille ja sukupuolille yms
# mutta keskiarvo on spesifi näille ja kysymykselle.

#qlen <-  c(4,2,2,2,6,2,2,7,7,7,5,2,7,7,7,5) # Number of options in each question of surv
# qlen not needed when dbinom is not used.

agel
countryl
genderl
fisl

objects.store(survey, surv, agel, countryl, genderl, fisl)
cat("Data.frames survey and surv, and vectors agel, countryl, genderl and fisl were stored.\n")

Analyses

Descriptive statistics

Error creating thumbnail: Unable to save thumbnail to destination

Correlation matrix of all questions in the survey (answers converted to numbers).

Model must contain predictors such as country, gender, age etc. Maybe we should first study what determinants are important? Model must also contain determinants that would increase or decrease fish consumption. This should be conditional on the current consumption. How? Maybe we should look at principal coordinates analysis with all questions to see how they behave.

Also look at correlation table to see clusters.

Some obvious results:

If reports no fish eating, many subsequent answers are NA.
No vitamins correlates negatively with vitamin intake.
Unknown salmon correlates negatively with the types of salmon eaten.
Different age categories correlate with each other.

However, there are also meaningful negative correlations:

Country vs allergy
Country vs Norwegian salmon and Rainbow trout
Country vs not traditional.
Country vs recommendation awareness
Allergy vs economic wellbeing
Baltic salmon use (4 questions) vs Don't like taste and Not used to
All questions between Easy to cook ... Traditional dish

Meaningful positive correlations:

All questions between Baltic salmon ... Rainbow trout
How often Baltic salmon/herring/side salmon/side herring
How much Baltic salmon/herring/side salmon/side herring
Better availability ... Recommendation
All questions between Economic wellbeing...Personal aims
Omega3, Vitamin D, and Other vitamins

Model runs

Model run 13.3.2017
Model run 21.4.2017 [5] old code from Answer merged to this code and debugged

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# This is code Op_en7749/ on page [[Goherr: Fish consumption study]]

library(OpasnetUtils)
library(ggplot2)
library(reshape2)
library(car)
library(vegan)

objects.latest("Op_en7749", "preprocess2") # [[Goherr: Fish consumption study]]: survey, surv

############################### From a previous code on Answer

for(i in c(5:6, 16, 29:30, 46:49, 85:86, 95:98, 135)) {
  temp <- survey[!is.na(survey[[i]]),]
  p <- ggplot(temp, aes(x = temp[[i]])) + geom_bar() +
    theme_gray(base_size = 18) + theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.4)) +
    labs(title = colnames(temp[i])) + xlab("") + facet_wrap(~ Country)
  print(p)
}

temp <- melt(survey, measure.vars = 145:153, variable.name = "Changing.factor", value.name = "Impact")
levs <- c("-5 strongly disagree", "-4", "-3", "-2", "-1", "0 Neutral", "1", "2", "3", "4", "5 strongly agree", "I don't know")
temp$Impact <- factor(temp$Impact, levels = levs, labels = levs, ordered = TRUE)

ggplot(temp, aes(x = Impact, fill = Country)) + geom_bar(position = "dodge") + facet_wrap(~ Changing.factor)+
  theme_gray(base_size = 24) + theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.4))

surveytemp <- subset(survey, survey[[31]] == "Yes")

temp <- melt(surveytemp, measure.vars = 38:43, variable.name = "Variable", value.name = "Value")
ggplot(temp, aes(x = Value, fill = Country)) + geom_bar(position = "dodge") + facet_wrap(~ Variable)+
  theme_gray(base_size = 24) + labs(title = "Baltic salmon sources")

temp <- melt(surveytemp, measure.vars = 50:59, variable.name = "Variable", value.name = "Value")
ggplot(temp, aes(x = Value, fill = Country)) + geom_bar(position = "dodge") + facet_wrap(~ Variable)+
  theme_gray(base_size = 24) + labs(title = "Reasons to eat Baltic salmon")

temp <- melt(surveytemp, measure.vars = 73:82, variable.name = "Variable", value.name = "Value")
ggplot(temp, aes(x = Value, fill = Country)) + geom_bar(position = "dodge") + facet_wrap(~ Variable)+
  theme_gray(base_size = 24) + theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.4)) + labs(title = "Baltic salmon actions")

surveytemp <- subset(survey, survey[[31]] == "No")

temp <- melt(surveytemp, measure.vars = 62:70, variable.name = "Variable", value.name = "Value")
ggplot(temp, aes(x = Value, fill = Country)) + geom_bar(position = "dodge") + facet_wrap(~ Variable)+
  theme_gray(base_size = 24) + labs(title = "Reasons not to eat Baltic salmon")


surveytemp <- subset(survey, survey[[86]] == "Yes")

temp <- melt(surveytemp, measure.vars = 87:92, variable.name = "Variable", value.name = "Value")
ggplot(temp, aes(x = Value, fill = Country)) + geom_bar(position = "dodge") + facet_wrap(~ Variable)+
  theme_gray(base_size = 24) + labs(title = "Baltic herring sources")

temp <- melt(surveytemp, measure.vars = 99:108, variable.name = "Variable", value.name = "Value")
ggplot(temp, aes(x = Value, fill = Country)) + geom_bar(position = "dodge") + facet_wrap(~ Variable)+
  theme_gray(base_size = 24) + labs(title = "Reasons to eat Baltic herring")

temp <- melt(surveytemp, measure.vars = 123:132, variable.name = "Variable", value.name = "Value")
ggplot(temp, aes(x = Value, fill = Country)) + geom_bar(position = "dodge") + facet_wrap(~ Variable)+
  theme_gray(base_size = 24) + theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.4)) + labs(title = "Baltic herring actions")

surveytemp <- subset(survey, survey[[86]] == "No")

temp <- melt(surveytemp, measure.vars = 111:120, variable.name = "Variable", value.name = "Value")
ggplot(temp, aes(x = Value, fill = Country)) + geom_bar(position = "dodge") + facet_wrap(~ Variable)+
  theme_gray(base_size = 24) + labs(title = "Reasons not to eat Baltic herring")

#####################################3

temp <- sapply(survey, as.numeric) # Can be done for surv to get a smaller matrix

survey_correlations <- (cor(temp, method="spearman", use="pairwise.complete.obs"))

temp <- colnames(survey_correlations)

melted_correlations <- melt(survey_correlations)

melted_correlations$Var1 <- factor(melted_correlations$Var1, levels=temp)
melted_correlations$Var2 <- factor(melted_correlations$Var2, levels=temp)
melted_correlations$value <- ifelse(melted_correlations$value >= 0.99,NA,melted_correlations$value)

ggplot(melted_correlations, aes(x = Var1, y = Var2, fill = value, label= round(value, 2)))+
  geom_raster()+
  theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.4))+
  scale_fill_gradient2(low = "#480610", mid = "#FFFFFF", high = "#06480F", midpoint = 0, space = "Lab", guide = "colourbar")

####################### Descriptive statistics

oprint(cor(surv, use = "pairwise.complete.obs"))
# --> Baltic salmon and herring eating are correlated, so they should be estimated together

oprint(table(surv[c(12,7,4)], useNA = "ifany"))
oprint(table(surv[c(13,12)], useNA = "ifany"))

############################# Plot original data

# Eating frequencies of fish and Baltic salmon and herring with random noise, all
pl <- surv[surv$Eatfish,c(5,8,10,13,15)]
scatterplotMatrix(
  data.matrix(pl) + runif(nrow(pl)*ncol(pl), -0.5, 0.5)
)

ggplot(data.frame(
  X = rep(1,5), Y = 5:1,
  legend = c("All", "Finland", "Sweden", "Denmark", "Estonia")
), aes(x=X, y=Y, label=legend))+
  geom_text()+
  labs(title="Fish eating questions with random noise")


## Fish eating questions with some random noise, all
pl <- surv[surv$Eatfish,c(5,6,7,12)]
scatterplotMatrix(
  data.matrix(pl) + runif(nrow(pl)*ncol(pl), -0.5, 0.5)
)

## Fish eating questions with some random noise, FI
pl <- surv[surv$Country == 1 & surv$Eatfish,c(5,6,7,12)]
scatterplotMatrix(
  data.matrix(pl) + runif(nrow(pl)*ncol(pl), -0.5, 0.5)
)

## Fish eating questions with some random noise, SWE
pl <- surv[surv$Country == 2 & surv$Eatfish,c(5,6,7,12)]
scatterplotMatrix(
  data.matrix(pl) + runif(nrow(pl)*ncol(pl), -0.5, 0.5)
)

## Fish eating questions with some random noise, Dk
pl <- surv[surv$Country == 3 & surv$Eatfish,c(5,6,7,12)]
scatterplotMatrix(
  data.matrix(pl) + runif(nrow(pl)*ncol(pl), -0.5, 0.5)
)

## Fish eating questions with some random noise, EST
pl <- surv[surv$Country == 4 & surv$Eatfish,c(5,6,7,12)]
scatterplotMatrix(
  data.matrix(pl) + runif(nrow(pl)*ncol(pl), -0.5, 0.5)
)

## Baltic herring questions with some random noise
pl <- surv[surv$Eatherr,13:16]
scatterplotMatrix(
  data.matrix(pl) + runif(nrow(pl)*ncol(pl), -0.5, 0.5)
)

## Baltic salmon questions with some random noise
pl <- surv[surv$Eatsalm,8:11]
scatterplotMatrix(
  data.matrix(pl) + runif(nrow(pl)*ncol(pl), -0.5, 0.5)
)

##################### CORRELATION MATRIX

temp <- sapply(survey, as.numeric) # Can be done for surv to get a smaller matrix

survey_correlations <- (cor(temp, method="spearman", use="pairwise.complete.obs"))

temp <- colnames(survey_correlations)

melted_correlations <- melt(survey_correlations)

melted_correlations$Var1 <- factor(melted_correlations$Var1, levels=temp)
melted_correlations$Var2 <- factor(melted_correlations$Var2, levels=temp)
melted_correlations$value <- ifelse(melted_correlations$value >= 0.99,NA,melted_correlations$value)

ggplot(melted_correlations, aes(x = Var1, y = Var2, fill = value, label= round(value, 2)))+
  geom_raster()+
  theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.4))+
  scale_fill_gradient2(low = "#480610", mid = "#FFFFFF", high = "#06480F", midpoint = 0, space = "Lab", guide = "colourbar")

############################### PRINCIPAL COORDINATE ANALYSIS (PCoA)

#tämä osa valmistaa sen datan.
hypocols1 <- c(46:49,95:98)
answ <- sapply(survey[hypocols1], FUN=as.numeric)
answ <- as.matrix(answ[!is.na(rowSums(answ)),])

pcoa_caps <- capscale(t(answ) ~ 1, distance="euclidean") ##PCoA done

## Kuva koko hypoteeseista

colstr <- c("palevioletred1","royalblue1","seagreen1","violet","khaki2","skyblue", "orange")

#hypo_sizes <- (5 - colMeans(answ))
#leg_sizes <- c(4, 3, 2, 1, 0.01)

#pdf(file="pcoa_plot.pdf", height=6, width=7.5)
plot(pcoa_caps, display = c("sp", "wa"), type="n")#, xlim=c(-6,4.5)) ## PCoA biplot, full scale
points(pcoa_caps, display= c("sp"), col="gray40") # adding the people points
points(pcoa_caps, display= c("wa"), pch=19)#, cex=hypo_sizes, col=trait.cols)
text(pcoa_caps, display=c("wa"), srt=25, cex=0.5)
#legend(x=-6, y=3.8, levels(traits), fill=colstr, bty="n", cex=1)
#legend(-6, -2, legend=c("Very likely", "Moderately likely",
#                        "No opinion", "Moderately unlikely", "Very unlikely"),
#       pch=21, pt.cex = leg_sizes, bty="n", cex=1)
#dev.off()

Bayes model

Model run 3.3.2017. All variables assumed independent. [6]
Model run 3.3.2017. p has more dimensions. [7]
Model run 25.3.2017. Several model versions: strange binomial+multivarnormal, binomial, fractalised multivarnormal [8]
Model run 27.3.2017 [9]
Other models except multivariate normal were archived and removed from active code 29.3.2017.
Model run 29.3.2017 with raw data graphs [10]
Model run 29.3.2017 with salmon and herring ovariables stored [11]
Model run 13.4.2017 with first version of coordinate matrix and principal coordinate analysis [12]
Model run 20.4.2017 [13] code works but needs a safety check against outliers
Model run 21.4.2017 [14] some model results plotted
Model run 21.4.2017 [15] ovariables produced by the model stored.
Model run 18.5.2017 [16] small updates

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# This is code Op_en7749/bayes on page [[Goherr: Fish consumption study]]

library(OpasnetUtils)
library(ggplot2)
library(reshape2)
library(rjags)
library(car)
library(vegan)
library(MASS)
#library(gridExtra) # Error: package ‘gridExtra’ was built before R 3.0.0: please re-install it

# Fish intake in humans
# Data from data.frame survey from page [[Goherr: Fish consumption study]]

objects.latest("Op_en7749", "preprocess2") # [[Goherr: Fish consumption study]]: survey, surv, ...

cat("Version with multivariate normal.\n")

# Development needs:
## Correlation between salmon.often and herring.often needs to be estimated.
## Gender, country and age-spesific values should be estimated.

mod <- textConnection("
  model{
    for(i in 1:S) {
      survs[i,1:4] ~ dmnorm(mus[], Omegas[,])
    }
    for(j in 1:H) {
      survh[j,1:4] ~ dmnorm(muh[], Omegah[,])
    }
    mus[1:4] ~ dmnorm(mu0[1:4], S2[1:4,1:4])
    Omegas[1:4,1:4] ~ dwish(S3[1:4,1:4],S)
    anss.pred ~ dmnorm(mus[], Omegas[,])
    muh[1:4] ~ dmnorm(mu0[1:4], S2[1:4,1:4])
    Omegah[1:4,1:4] ~ dwish(S3[1:4,1:4],H)
    ansh.pred ~ dmnorm(muh[], Omegah[,])
  }
")

jags <- jags.model(
  mod,
  data = list(
    survs = surv[surv$Eatsalm,c(8:11)],
    S = sum(surv$Eatsalm),
    survh = surv[surv$Eatherr,c(13:16)],
    H = sum(surv$Eatherr),
    mu0 = rep(2,4),
    S2 = diag(4)/100000,
    S3 = diag(4)/10000
  ),
  n.chains = 4,
  n.adapt = 100
)

update(jags, 100)
samps.j <- jags.samples(
  jags, 
  c('mus', 'Omegas', 'anss.pred','muh','Omegah','ansh.pred'), 
  1000
)
js <- array(
  c(
    samps.j$mus[,,1],
    samps.j$Omegas[,1,,1],
    samps.j$Omegas[,2,,1],
    samps.j$Omegas[,3,,1],
    samps.j$Omegas[,4,,1],
    samps.j$anss.pred[,,1],
    samps.j$muh[,,1],
    samps.j$Omegah[,1,,1],
    samps.j$Omegah[,2,,1],
    samps.j$Omegah[,3,,1],
    samps.j$Omegah[,4,,1],
    samps.j$ansh.pred[,,1]
  ),
  dim = c(4,1000,6,2),
  dimnames = list(
    Question = 1:4,
    Iter = 1:1000,
    Parameter = c("mu","Omega1", "Omega2", "Omega3", "Omega4", "ans.pred"),
    Fish = c("Salmon", "Herring")
  )
)

# Mu for all questions about salmon
scatterplotMatrix(t(js[,,1,1]))
# All parameters for question 1 about salmon
scatterplotMatrix(js[1,,,1])
# Same for herring
scatterplotMatrix(js[1,,,2])

jsd <- melt(js)
#ggplot(jsd, aes(x=value, colour=Question))+geom_density()+facet_grid(Parameter ~ Fish)
#ggplot(as.data.frame(js), aes(x = anss.pred, y = Sampled))+geom_point()+stat_ellipse()

coda.j <- coda.samples(
  jags, 
  c('mus', 'Omegas', 'anss.pred'), 
  1000
)

plot(coda.j)

######## fish.param contains expected values of the distribution parameters from the model

fish.param <- list(
  mu = apply(js[,,1,], MARGIN = c(1,3), FUN = mean),
  Omega = lapply(
    1:2,
    FUN = function(x) {
      solve(apply(js[,,2:5,], MARGIN = c(1,3,4), FUN = mean)[,,x])
    } # solve matrix: precision->covariace
  )
)

objects.store(fish.param)
cat("List fish.param stored.\n")

Initiate ovariables

Amount estimated from a bayesian model.

Model run 24.5.2017 [17]

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# This is code Op_en7749/modeljsp on page [[Goherr: Fish consumption study]]

library(OpasnetUtils)

jsp <- Ovariable(
  "jsp",
  dependencies = data.frame(Name = "fish.param", Ident = "Op_en7749/bayes"),
  formula = function(...) {
    require(MASS)
    require(reshape2)
    jsp <- lapply(
      1:2,
      FUN = function(x) {
        mvrnorm(openv$N, fish.param$mu[,x], fish.param$Omega[[x]])
      }
    )
    
    jsp <- rbind(
      cbind(
        Fish = "Salmon",
        Iter = 1:nrow(jsp[[1]]),
        as.data.frame(jsp[[1]])
      ),
      cbind(
        Fish = "Herring",
        Iter = 1:nrow(jsp[[2]]),
        as.data.frame(jsp[[2]])
      )
    )
    jsp <- melt(jsp, id.vars = c("Iter", "Fish"), variable.name = "Question", value.name = "Result")
    jsp <- Ovariable(output=jsp, marginal = colnames(jsp) %in% c("Iter", "Fish", "Question"))
    return(jsp)
  }
)

objects.store(jsp)
cat("Ovariable jsp stored.\n")

Amount estimates directly from data rather than from a bayesian model.

Initiation run 18.5.2017 [18]

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# This is code Op_en7749/surveyjsp on page [[Goherr: Fish consumption study]]
# The code produces amount esimates (jsp ovariable) directly from data rather than bayesian model.

library(OpasnetUtils)
library(reshape2)

objects.latest("Op_en7749", code_name="preprocess2") # original survey data (surv)

sur <- survey[c(157,1,3,158,16,29,30,31,46:49,86,95:98)]

#colnames(sur)
#[1] "Row"               "Country"           "Gender"            "Ages"             
#[5] "Eat.fish"          "How.often.fish"    "Eat.salmon"        "Baltic.salmon"    
#[9] "How.often.BS"      "How.much.BS"       "How.often.side.BS" "How.much.side.BS" 
#[13] "Eat.BH"            "How.often.BH"      "How.much.BH"       "How.often.side.BH"
#[17] "How.much.side.BH" 

colnames(sur)[c(1,8:17)] <- c("Iter",rep(as.character(c(5,1:4)),2))
sur[8:17] <- sapply(sur[8:17], as.numeric)
sur <- rbind(cbind(Fish="Herring", sur[-(8:12)]),
             cbind(Fish="Salmon", sur[-(13:17)])
)
sur <- melt(
  sur,
  measure.vars=as.character(1:5),
  variable.name="Question",
  value.name="Result"
)
sur$Result[is.na(sur$Result)] <- 1 # Ovariable often becomes never -> amount becomes 0.

jsp <- Ovariable(
  "jsp", 
  output = sur, 
  marginal = colnames(sur) %in% c("Fish", "Iter", "Question")
)

objects.store(jsp)
cat("Ovariable jsp with actual survey data: each respondent is an iteration.\n")

Initiate other ovariables

Code stores ovariables assump, often, much, oftenside, muchside, amount.
Model run 19.5.2017 [19]
Initiation run 24.5.2017 without jsp [20]
Model run 8.6.2017 [21]

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# This is code Op_en7749/initiate on page [[Goherr: Fish consumption study]]

library(OpasnetUtils)

# Combine modelled survey answers with estimated amounts and frequencies by:
# Rounding the modelled result and merging that with value in ovariable assump

often <- Ovariable(
  "often",
  dependencies = data.frame(Name=c("jsp","assump")),
  formula = function(...) {
    out <- jsp[jsp$Question == "1" , !colnames(jsp@output) %in% c("Question")]
    out$Value <- round(result(out))
    out <- merge(
      assump@output[assump$Variable == "freq",],
      out@output
    )
    out <- out[!colnames(out) %in% c("Value", "Variable", "Result")]
    colnames(out)[colnames(out) == "assumpResult"] <- "Result"
    return(out)
  }
)

much <- Ovariable(
  "much",
  dependencies = data.frame(Name=c("jsp","assump")),
  formula = function(...) {
    out <- jsp[jsp$Question == "2" , !colnames(jsp@output) %in% c("Question")]
    out$Value <- round(result(out))
    out <- merge(
      assump@output[assump$Variable == "amdish",],
      out@output
    )
    out <- out[!colnames(out) %in% c("Value", "Variable", "Result")]
    colnames(out)[colnames(out) == "assumpResult"] <- "Result"
    return(out)
  }
)

oftenside <- Ovariable(
  "oftenside",
  dependencies = data.frame(Name=c("jsp","assump")),
  formula = function(...) {
    out <- jsp[jsp$Question == "3" , !colnames(jsp@output) %in% c("Question")]
    out$Value <- round(result(out))
    out <- merge(
      assump@output[assump$Variable == "freq",],
      out@output
    )
    out <- out[!colnames(out) %in% c("Value", "Variable", "Result")]
    colnames(out)[colnames(out) == "assumpResult"] <- "Result"
    return(out)
  }
)

muchside <- Ovariable(
  "muchside",
  dependencies = data.frame(Name=c("jsp","assump")),
  formula = function(...) {
    out <- jsp[jsp$Question == "4" , !colnames(jsp@output) %in% c("Question")]
    out$Value <- round(result(out))
    out <- merge(
      assump@output[assump$Variable == "amside",],
      out@output
    )
    out <- out[!colnames(out) %in% c("Value", "Variable", "Result")]
    colnames(out)[colnames(out) == "assumpResult"] <- "Result"
    return(out)
  }
)

assump <- Ovariable(
  "assump",
  ddata = "Op_en7749", subset = "Assumptions for calculations"
)

amount <- Ovariable(
  "amount",
  dependencies = data.frame(Name = c(
    "often",
    "much",
    "oftenside",
    "muchside",
    "assump"
  )),
  formula = function(...) {
    away <- c(
      "assumpUnit", 
      "Eat.fish",
      "How.often.fish",
      "Eat.salmon"
    )
    often <- often[ , !colnames(often@output) %in% away]
    much <- much[ , !colnames(much@output) %in% away]
    oftenside <- oftenside[ , !colnames(oftenside@output) %in% away]
    muchside <- muchside[ , !colnames(muchside@output) %in% away]
    assump <- assump[assump$Variable == "ingredient", !colnames(assump@output) %in%
       c("Variable", "Value", "Explanation", "assumpUnit")]

    out <- (often * much + oftenside * muchside * assump)/365 # g /d
    return(out)
  }
)

objects.store(assump, often, much, oftenside, muchside, amount)
cat("Ovariables assump, often, much, oftenside, muchside, amount stored.\n")

Dependencies

The survey data will be used as input in the benefit-risk assessment of Baltic herring and salmon intake, which is part of the WP5 work in Goherr-project.

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References

Related files

Goherr: Fish consumption study. Opasnet . [22]. Accessed 18 May 2024.

Difference between revisions of "Goherr: Fish consumption study"

Latest revision as of 10:12, 8 June 2017

Contents

Question

Answer

Rationale

Data

Questionnaire

Assumptions

Preprocessing

Analyses

Descriptive statistics

Bayes model

Initiate ovariables

Dependencies

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References

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