washb_ttest | R Documentation |
Function to call the paired t-test for two different arms of the study.
washb_ttest(Y,tr,strat,contrast)
Y |
quantitative outcome variable (e.g. LAZ) |
tr |
binary treatment group variable, comparison group first |
strat |
stratification variable (here: block) |
contrast |
vector of length 2 that includes the tr groups to contrast |
washb_ttest
estimates a paired t-test for differences in means paired within randomization blocks.
The arguments Y
,tr
, and strat
need to be from the same dataset.
Returns a vector with the mean difference (diff), 95 percent confidence intervals (ci.lb and ci.ub), t-statistic (t-stat), and p-value (p) for the paired t-test
## Not run:
#The washb_ttest function
#Load in Bangladesh anthropometry data.
data(washb_bangladesh_enrol)
washb_bangladesh_enrol <- washb_bangladesh_enrol
data(washb_bangladesh_anthro)
washb_bangladesh_anthro <- washb_bangladesh_anthro
washb_bangladesh_enrol$svydate <- NULL
washb_bangladesh_enrol$month <- NULL
laz <- merge(washb_bangladesh_enrol,washb_bangladesh_anthro,by=c("dataid","clusterid","block","tr"),all.x=F,all.y=T)
# subset to the endline target children
laz <- subset(laz,svy==2)
laz <- subset(laz,tchild=="Target child")
# Drop children with extreme LAZ values
laz <- subset(laz,laz_x!=1)
laz$tr <- factor(laz$tr,levels=c("Control","Water","Sanitation","Handwashing","WSH","Nutrition","Nutrition + WSH"))
#Run paired ttest function for water vs. control comparison:
washb_ttest(Y=laz$laz,tr=laz$tr,strat=laz$block, contrast=c("Control","Water"))
## End(Not run)
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