I want to create a summary statistics table which reports the mean/median for each variable by region, and in the rows compare the statistic between US born and immigrants in the sample, as well as overall. I don't know the code that can allow me to group the table in multiple ways.
Here is the code I have come up with so far:
#the data frame
structure(list(AGE = c(40L, 23L, 24L, 18L, 30L, 33L, 32L, 63L,
22L, 24L), FAMSIZE = c(2L, 2L, 2L, 3L, 2L, 6L, 2L, 1L, 2L, 1L
), HYPERTEN = c(0, 0, 0, 0, 0, 0, 0, 1, 0, 0), ALC = c(0, 2,
3, 0, 2, 0, 3, 0, 2, 2), region_group = c("Region 4", "Region 3",
"Region 4", "Region 3", "Region 1", "Region 2", "Region 1", "Region 2",
"Region 4", "Region 4"), PSU = c(2L, 1L, 2L, 2L, 2L, 1L, 2L,
2L, 1L, 2L), IMMIGRANT = c(0, 0, 0, 0, 0, 1, 0, 0, 0, 1), SAMPWEIGHT_MERGE = c(65, 860.4,
94.4, 9146, 170.8, 310.4, 755.2, 1053.4, 3964.4, 706.2), STRATA = c(6296L,
6165L, 6296L, 6224L, 6045L, 6083L, 6029L, 6073L, 6287L, 6247L
)), row.names = c(NA, 10L), class = "data.frame")
#weighting data frame so accounts for sample design
sample_survey<- as_survey_design(A, ids=PSU, weights=SAMPWEIGHT_MERGE, strata=STRATA, nest=TRUE)
options(survey.lonely.psu="remove")
#producing desired table
out1<-sample_survey %>%
group_by(region_group) %>%
summarise("Number of drinks (mean)"=survey_mean(ALC),
"Number of drinks (median)"=survey_median(ALC),"Hypertension"=survey_mean(HYPERTEN), "Family Size"=survey_mean(FAMSIZE), "Age"=survey_median(AGE))
out1=t(out1)
out1
#But here is what I hope the table can look like, such that the mean/median amongst all individuals, immigrant=0 and the immigrant=1 group are all displayed for each variable
[,1] [,2] [,3] [,4]
region_group "Region 1" "Region 2" "Region 3" "Region 4"
Number of drinks (all) "1.663778" "2.131566" "1.744107" "2.009594"
IMMIGRANT==0
IMMIGRANT==1
Number of drinks (mean)_se "0.1375124" "0.1245772" "0.0957500" "0.1199982"
Number of drinks (all) "1" "2" "1" "2"
IMMIGRANT==0
IMMIGRANT==1
Number of drinks (median)_se "0.0000000" "0.2531528" "0.0000000" "0.2533324"
Hypertension (all) "0.1340147" "0.1685102" "0.1834528" "0.1225418"
IMMIGRANT==0
IMMIGRANT==1
Hypertension_se "0.01623974" "0.01529678" "0.01463019" "0.01475651"
Family \n (all) Size "3.121062" "2.883905" "3.107202" "3.265012"
IMMIGRANT==0
IMMIGRANT==1
Family \n Size_se "0.11668906" "0.07435704" "0.08004129" "0.11138869"
Age (all) "30" "27" "30" "28"
IMMIGRANT==0
IMMIGRANT==1
Age_se "1.3615690" "1.0126110" "0.7616152" "0.7599972"
Thank you!
You could use the tables package :
library(tables)
tables::tabular((ALC+HYPERTEN)*(IMMIGRANT=factor(IMMIGRANT)+1)*(weighted.mean+median)*Arguments(w = SAMPWEIGHT_MERGE)~(region=factor(region_group)), data=data)
region
IMMIGRANT Region 1 Region 2 Region 3
ALC 0 weighted.mean 2.816 0.0000 0.172
median 2.500 0.0000 1.000
1 weighted.mean NaN 0.0000 NaN
median NA 0.0000 NA
All weighted.mean 2.816 0.0000 0.172
median 2.500 0.0000 1.000
HYPERTEN 0 weighted.mean 0.000 1.0000 0.000
median 0.000 1.0000 0.000
1 weighted.mean NaN 0.0000 NaN
median NA 0.0000 NA
All weighted.mean 0.000 0.7724 0.000
median 0.000 0.5000 0.000