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## cohen.d### Import alldata used for birthorder
alldata_birthorder = readRDS("data/alldata_birthorder.rds")Number of individuals we were able to reconstruct the three different birth orders based on pregnancy and marriage history for
## Count Birthorder
n_birthorder = alldata_birthorder %>%
summarise(Maternal_Birth_Order = sum(!is.na(birthorder_uterus_alive)),
Maternal_Pregnancy_Order = sum(!is.na(birthorder_uterus_preg)),
Parental_Full_Sibling_Birth_Order = sum(!is.na(birthorder_genes)),
Naive_Maternal_Birth_Order = sum(!is.na(birthorder_naive)))
n_birthorder| Maternal_Birth_Order | Maternal_Pregnancy_Order | Parental_Full_Sibling_Birth_Order | Naive_Maternal_Birth_Order |
|---|---|---|---|
| 43322 | 48546 | 42682 | 67026 |
n_birthorder = alldata_birthorder %>%
summarise(Maternal_Birth_Order = sum(!is.na(birthorder_uterus_alive) & any_multiple_birth != 1,
na.rm = T),
Maternal_Pregnancy_Order = sum(!is.na(birthorder_uterus_preg) & any_multiple_birth != 1,
na.rm = T),
Parental_Full_Sibling_Birth_Order = sum(!is.na(birthorder_genes) & any_multiple_birth != 1,
na.rm = T),
Naive_Maternal_Birth_Order = sum(!is.na(birthorder_naive) & (is.na(any_multiple_birth) | any_multiple_birth != 1),
na.rm = T))
n_birthorder| Maternal_Birth_Order | Maternal_Pregnancy_Order | Parental_Full_Sibling_Birth_Order | Naive_Maternal_Birth_Order |
|---|---|---|---|
| 40189 | 45034 | 39589 | 63451 |
## Count Birthorder - without only children
n_birthorder = alldata_birthorder %>%
summarise(Maternal_Birth_Order = sum(!is.na(birthorder_uterus_alive) & any_multiple_birth != 1 &
sibling_count_uterus_alive != 1,
na.rm = T),
Maternal_Pregnancy_Order = sum(!is.na(birthorder_uterus_preg) & any_multiple_birth != 1 &
sibling_count_uterus_preg != 1,
na.rm = T),
Parental_Full_Sibling_Birth_Order = sum(!is.na(birthorder_genes) & any_multiple_birth != 1 &
sibling_count_genes != 1,
na.rm = T),
Naive_Maternal_Birth_Order = sum(!is.na(birthorder_naive) & any_multiple_birth != 1 &
sibling_count_naive != 1,
na.rm = T))
n_birthorder| Maternal_Birth_Order | Maternal_Pregnancy_Order | Parental_Full_Sibling_Birth_Order | Naive_Maternal_Birth_Order |
|---|---|---|---|
| 36014 | 41204 | 34786 | 41692 |
## Count Birthorder - without only children
alldata_birthorder = alldata_birthorder %>%
mutate(alive = ifelse(!is.na(g_factor_2015_old), 1, alive)) # for seven people its reported that they are not alive anymore but they participated in IFLS5 ?
n_birthorder = alldata_birthorder %>%
summarise(Maternal_Birth_Order = sum(!is.na(birthorder_uterus_alive) & any_multiple_birth != 1 &
sibling_count_uterus_alive != 1 & alive != 3,
na.rm = T),
Maternal_Pregnancy_Order = sum(!is.na(birthorder_uterus_preg) & any_multiple_birth != 1 &
sibling_count_uterus_preg != 1 & alive != 3,
na.rm = T),
Parental_Full_Sibling_Birth_Order = sum(!is.na(birthorder_genes) & any_multiple_birth != 1 &
sibling_count_genes != 1 & alive != 3,
na.rm = T))
n_birthorder| Maternal_Birth_Order | Maternal_Pregnancy_Order | Parental_Full_Sibling_Birth_Order |
|---|---|---|
| 32714 | 33678 | 31635 |
### All people in the birthorder data file that have ANY g-factor, educational attainment, personality or risk values have to be marked
alldata_birthorder = alldata_birthorder %>%
mutate(used_any = ifelse(!is.na(g_factor_2015_old) | !is.na(g_factor_2015_young) | !is.na(g_factor_2007_old) |
!is.na(g_factor_2007_young) | !is.na(big5_ext) | !is.na(big5_open) | !is.na(big5_agree) |
!is.na(big5_neu) | !is.na(big5_con) | !is.na(riskA) | !is.na(riskB) |
is.na(years_of_education), 1, 0))
n_birthorder = alldata_birthorder %>%
summarise(Maternal_Birth_Order = sum(!is.na(birthorder_uterus_alive) & any_multiple_birth != 1 &
sibling_count_uterus_alive != 1 & alive != 3 &
used_any == 1,
na.rm = T),
Maternal_Pregnancy_Order = sum(!is.na(birthorder_uterus_preg) & any_multiple_birth != 1 &
sibling_count_uterus_preg != 1 & alive != 3 &
used_any == 1,
na.rm = T),
Parental_Full_Sibling_Birth_Order = sum(!is.na(birthorder_genes) & any_multiple_birth != 1 &
sibling_count_genes != 1 & alive != 3 &
used_any == 1,
na.rm = T),
Naive_Maternal_Birth_Order = sum(!is.na(birthorder_naive) & (is.na(any_multiple_birth) | any_multiple_birth != 1) &
sibling_count_naive != 1 & alive != 3 &
used_any == 1,
na.rm = T)
)
n_birthorder| Maternal_Birth_Order | Maternal_Pregnancy_Order | Parental_Full_Sibling_Birth_Order | Naive_Maternal_Birth_Order |
|---|---|---|---|
| 32643 | 33606 | 31566 | 41693 |
### All people in the birthorder data file that have all Intelligence measurements
alldata_birthorder = alldata_birthorder %>%
mutate(used_iq = ifelse(!is.na(g_factor_2015_old) | !is.na(g_factor_2015_young) | !is.na(g_factor_2007_old) |
!is.na(g_factor_2007_young), 1, 0)) # used_iq = 1:included, 0:not_included
n_birthorder = alldata_birthorder %>%
summarise(Maternal_Birth_Order = sum(!is.na(birthorder_uterus_alive) & any_multiple_birth != 1 &
sibling_count_uterus_alive != 1 & alive != 3 &
used_iq == 1,
na.rm = T),
Maternal_Pregnancy_Order = sum(!is.na(birthorder_uterus_preg) & any_multiple_birth != 1 &
sibling_count_uterus_preg != 1 & alive != 3 &
used_iq == 1,
na.rm = T),
Parental_Full_Sibling_Birth_Order = sum(!is.na(birthorder_genes) & any_multiple_birth != 1 &
sibling_count_genes != 1 & alive != 3 &
used_iq == 1,
na.rm = T))
n_birthorder| Maternal_Birth_Order | Maternal_Pregnancy_Order | Parental_Full_Sibling_Birth_Order |
|---|---|---|
| 12503 | 12631 | 12193 |
### All people in the birthorder data file that have Personality Measurements
missingness_patterns(alldata_birthorder %>% select(big5_ext, big5_con, big5_open, big5_neu, big5_agree, big5_open))## index col missings
## 1 big5_ext 69795
## 2 big5_con 69795
## 3 big5_open 69795
## 4 big5_neu 69795
## 5 big5_agree 69795| Pattern | Freq | Culprit |
|---|---|---|
| 1_2_3_4_5 | 69795 | |
| _________ | 31446 | _ |
# Missingness Pattern shows that if one of the personality measurements is missing all Measurements are missing
alldata_birthorder = alldata_birthorder %>%
mutate(used_pers = ifelse(!is.na(big5_ext), 1, 0))
n_birthorder = alldata_birthorder %>%
summarise(Maternal_Birth_Order = sum(!is.na(birthorder_uterus_alive) & any_multiple_birth != 1 &
sibling_count_uterus_alive != 1 & alive != 3 &
used_pers == 1,
na.rm = T),
Maternal_Pregnancy_Order = sum(!is.na(birthorder_uterus_preg) & any_multiple_birth != 1 &
sibling_count_uterus_preg != 1 & alive != 3 &
used_pers == 1,
na.rm = T),
Parental_Full_Sibling_Birth_Order = sum(!is.na(birthorder_genes) & any_multiple_birth != 1 &
sibling_count_genes != 1 & alive != 3 &
used_pers == 1,
na.rm = T))
n_birthorder| Maternal_Birth_Order | Maternal_Pregnancy_Order | Parental_Full_Sibling_Birth_Order |
|---|---|---|
| 5922 | 5976 | 5803 |
### All people in the birthorder data file that have Risk Measurements
missingness_patterns(alldata_birthorder %>% select(riskA, riskB))## index col missings
## 1 riskA 73461
## 2 riskB 71663| Pattern | Freq | Culprit |
|---|---|---|
| 1_2 | 70149 | |
| ___ | 26266 | _ |
| 1__ | 3312 | riskA |
| __2 | 1514 | riskB |
## Missingness Pattern shows that sometimes A and sometimes B is missing
alldata_birthorder = alldata_birthorder %>%
mutate(used_riskA = ifelse(!is.na(riskA), 1, 0),
used_riskB = ifelse(!is.na(riskB), 1, 0))
n_birthorder = alldata_birthorder %>%
summarise(Maternal_Birth_Order = sum(!is.na(birthorder_uterus_alive) & any_multiple_birth != 1 &
sibling_count_uterus_alive != 1 & alive != 3 &
used_riskA == 1,
na.rm = T),
Maternal_Pregnancy_Order = sum(!is.na(birthorder_uterus_preg) & any_multiple_birth != 1 &
sibling_count_uterus_preg != 1 & alive != 3 &
used_riskA == 1,
na.rm = T),
Parental_Full_Sibling_Birth_Order = sum(!is.na(birthorder_genes) & any_multiple_birth != 1 &
sibling_count_genes != 1 & alive != 3 &
used_riskA == 1,
na.rm = T))
n_birthorder| Maternal_Birth_Order | Maternal_Pregnancy_Order | Parental_Full_Sibling_Birth_Order |
|---|---|---|
| 5331 | 5383 | 5230 |
n_birthorder = alldata_birthorder %>%
summarise(Maternal_Birth_Order = sum(!is.na(birthorder_uterus_alive) & any_multiple_birth != 1 &
sibling_count_uterus_alive != 1 & alive != 3 &
used_riskB == 1,
na.rm = T),
Maternal_Pregnancy_Order = sum(!is.na(birthorder_uterus_preg) & any_multiple_birth != 1 &
sibling_count_uterus_preg != 1 & alive != 3 &
used_riskB == 1,
na.rm = T),
Parental_Full_Sibling_Birth_Order = sum(!is.na(birthorder_genes) & any_multiple_birth != 1 &
sibling_count_genes != 1 & alive != 3 &
used_riskB == 1,
na.rm = T))
n_birthorder| Maternal_Birth_Order | Maternal_Pregnancy_Order | Parental_Full_Sibling_Birth_Order |
|---|---|---|
| 5603 | 5658 | 5490 |
### All people in the birthorder data file that have educational attainment measurements
missingness_patterns(alldata_birthorder %>% select(years_of_education))## index col missings
## 1 years_of_education 67423| Pattern | Freq | Culprit |
|---|---|---|
| 1 | 67423 | years_of_education |
| _ | 33818 | _ |
alldata_birthorder = alldata_birthorder %>%
mutate(used_ea = ifelse(!is.na(years_of_education), 1, 0))
n_birthorder = alldata_birthorder %>%
summarise(Maternal_Birth_Order = sum(!is.na(birthorder_uterus_alive) & any_multiple_birth != 1 &
sibling_count_uterus_alive != 1 & alive != 3 &
used_ea == 1,
na.rm = T),
Maternal_Pregnancy_Order = sum(!is.na(birthorder_uterus_preg) & any_multiple_birth != 1 &
sibling_count_uterus_preg != 1 & alive != 3 &
used_ea == 1,
na.rm = T),
Parental_Full_Sibling_Birth_Order = sum(!is.na(birthorder_genes) & any_multiple_birth != 1 &
sibling_count_genes != 1 & alive != 3 &
used_ea == 1,
na.rm = T))
n_birthorder| Maternal_Birth_Order | Maternal_Pregnancy_Order | Parental_Full_Sibling_Birth_Order |
|---|---|---|
| 6150 | 6209 | 6030 |