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Coalesce partner birth year and relationship start year data across w…
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explorations/examine_patterns_in_partner_data_across_waves.R
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| # Emily Cantrell | ||
| # Exploration of data about partner from LISS | ||
| library(tidyverse) | ||
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| # The purpose of this code is to determine which features about the partner requires us to | ||
| # coalesce data across waves. For example: | ||
| # (1) Partner's birthyear is only reported once. If the person remains with the same partner, the birthyear | ||
| # is not reported again in subsequent waves. Therefore, we need to coalesce data across waves. | ||
| # (2) Partner's gender is recorded repeatedly across waves even if there is no change. Therefore, | ||
| # we can use data from just the most recent wave (or a few waves), and don't need to coalesce across waves. | ||
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| # Read in the data | ||
| train_full <- read.csv("/Users/ecantrell/Documents/PreFer\ 2024/prefer_data/training_data/PreFer_train_data.csv") | ||
| outcome <- read.csv("/Users/ecantrell/Documents/PreFer\ 2024/prefer_data/training_data/PreFer_train_outcome.csv") | ||
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| # Filter to only people with non-missing outcomes | ||
| train <- train_full %>% | ||
| left_join(outcome) %>% | ||
| filter(!is.na(new_child)) | ||
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| # Do you currently have a partner? | ||
| train %>% | ||
| select(cf08a024, cf09b024, cf10c024, cf11d024, cf12e024, cf13f024, cf14g024, cf15h024, cf16i024, cf17j024, cf18k024, cf19l024, cf20m024) %>% | ||
| View() | ||
| # Decision: no need to coalesce across years; the same value is recorded repeatedly across waves | ||
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| # Do you live with that partner? | ||
| train %>% | ||
| select(cf08a025, cf09b025, cf10c025, cf11d025, cf12e025, cf13f025, cf14g025, cf15h025, cf16i025, cf17j025, cf18k025, cf19l025, cf20m025) %>% | ||
| View() | ||
| # Decision: no need to coalesce across years; the same value is recorded repeatedly across waves | ||
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| # What is his or her year of birth? | ||
| train %>% | ||
| select(cf20m024, cf08a026, cf09b026, cf10c026, cf11d026, cf12e026, cf13f026, cf14g026, cf15h026, cf16i026, cf17j026, cf18k026, cf19l026, cf20m026) %>% | ||
| View() | ||
| # Decision: the partner's birthyear seems to be only collected in one wave, but the wave varies by person depending | ||
| # when they started the survey or got together with the partner, so we should make a variable that takes the most | ||
| # recently reported partner birthyear (use the "coalesce" function). | ||
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| # In what country was your partner born? | ||
| train %>% | ||
| select(cf08a027, cf09b027, cf10c027, cf11d027, cf12e027, cf13f027, cf14g027, cf15h027, cf16i027, cf17j027, cf18k027, cf19l027, cf20m027) %>% | ||
| View() | ||
| train %>% group_by(cf08a027) %>% count() | ||
| # Decision: almost all partners were born in Netherlands or have NA for this question, so I won't use it | ||
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| # In what year did relationship begin? | ||
| train %>% | ||
| select(cf08a028, cf09b028, cf10c028, cf11d028, cf12e028, cf13f028, cf14g028, cf15h028, cf16i028, cf17j028, cf18k028, cf19l028, cf20m028) %>% | ||
| View() | ||
| # Decision: coalesce the data across years to get the most recently reported value | ||
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| # In what year did you start living with partner? | ||
| train %>% | ||
| select(cf08a029, cf09b029, cf10c029, cf11d029, cf12e029, cf13f029, cf14g029, cf15h029, cf16i029, cf17j029, cf18k029, cf19l029, cf20m029) %>% | ||
| View() | ||
| # Decision: no need to coalesce across years; the same value is recorded repeatedly across waves | ||
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| # Are you married? | ||
| train %>% | ||
| select(cf08a030, cf09b030, cf10c030, cf11d030, cf12e030, cf13f030, cf14g030, cf15h030, cf16i030, cf17j030, cf18k030, cf19l030, cf20m030) %>% | ||
| View() | ||
| # Decision: no need to coalesce across years; the same value is recorded repeatedly across waves | ||
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| # In what year did you marry? | ||
| train %>% | ||
| select(cf08a031, cf09b031, cf10c031, cf11d031, cf12e031, cf13f031, cf14g031, cf15h031, cf16i031, cf17j031, cf18k031, cf19l031, cf20m031) %>% | ||
| View() | ||
| # Decision: no need to coalesce across years; the same value is recorded repeatedly across waves | ||
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| # What is your partner's gender? | ||
| train %>% | ||
| select(cf20m024, cf08a032, cf09b032, cf10c032, cf11d032, cf12e032, cf13f032, cf14g032, cf15h032, cf16i032, cf17j032, cf18k032, cf19l032, cf20m032) %>% | ||
| View() | ||
| train %>% | ||
| group_by(cf20m024, is.na(cf20m032)) %>% | ||
| count() | ||
| train %>% | ||
| select(cf20m024, cf08a032, cf09b032, cf10c032, cf11d032, cf12e032, cf13f032, cf14g032, cf15h032, cf16i032, cf17j032, cf18k032, cf19l032, cf20m032) %>% | ||
| filter(cf20m024 == 1) %>% # Filter to people who currently have partner | ||
| View() | ||
| # Everyone who said they currently have a partner in 2020 has partner's gender reported in 2020 | ||
| # Decision: no need to coalesce across years | ||
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| #### Draft code for creating the variables #### | ||
| # I will insert a version of this code into submission.R | ||
| toy <- train %>% | ||
| mutate(partner_birth_year = coalesce(cf20m026, cf19l026, cf18k026, cf17j026, cf16i026, cf15h026, cf14g026, cf13f026, cf12e026, cf11d026, cf10c026, cf09b026, cf08a026)) | ||
| toy %>% | ||
| select(cf20m024, cf08a026, cf09b026, cf10c026, cf11d026, cf12e026, cf13f026, cf14g026, cf15h026, cf16i026, cf17j026, cf18k026, cf19l026, cf20m026, most_recent) %>% | ||
| View() | ||
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| toy <- train %>% | ||
| mutate(year_relationship_began = coalesce(cf20m028, cf19l028, cf18k028, cf17j028, cf16i028, cf15h028, cf14g028, cf13f028, cf12e028, cf11d028, cf10c028, cf09b028, cf08a028)) | ||
| toy %>% | ||
| select(cf20m028, cf19l028, cf18k028, cf17j028, cf16i028, cf15h028, cf14g028, cf13f028, cf12e028, cf11d028, cf10c028, cf09b028, cf08a028, year_relationship_began) %>% | ||
| View() |
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