tab_look: tab_look
In lorenc5/Rweights3: Rweights3 -- Poststratification Weighting

Description Usage Arguments Value Author(s) Examples

Prints table of “weight to” proportions, actual proportions (from unweighted or weighted data), absolute difference, and percent difference.

1	tab_look(vector1, vector2)

`vector1`	Numeric vector of proportions
`vector2`	Numeric vector of, ideally, weighted proportions

Matrix object of values, including columns of initial vector of “weight to” proportions, weighted proportions, absolute difference, and percent difference between vector1 and vector2.

Loren Collingwood <loren.collingwood@ucr.edu>

#NOT RUN: READ IN DATA
data (wapoll)

#NOT RUN: CREATE WEIGHT TO PROPORTIONS
weight_props_age <- weight_to(c(26.0,39.3,34.7), c("18-40","41-65","66+"))
weight_props_gender <- weight_to(c(49,51), c("Male","Female"))
weight_props_party <- weight_to(c(33.8,28.1,38.1), c("Dem","Rep","Ind"))
weight_props_region <- weight_to(c(53.5,20.6,25.8), c("Reg1-PS","Reg2-EW","Reg3-O"))

#NOT RUN: CREATE PROPORTIONS FROM DATA
age_current <- gen_survey_props(wapoll$age3) #1=18-40,2=41-65,3=66+; age3
gender_current <- gen_survey_props(wapoll$gender) #0=Male, 1=Female

#NOT RUN: CREATE WEIGHT TO AMOUNT
age_weight_to <- weight_amount(weight_props_age,age_current)
gender_weight_to <- weight_amount(weight_props_gender,gender_current)

#NOT RUN: CREATE AGE*GENDER WEIGHT
age_weight_2 <- variable_weight(wapoll$age3,age_weight_to)	
gender_weight_2 <- variable_weight(wapoll$gender,gender_weight_to)	
svyd_age_gender <- survey_weight(cbind(age_weight_2,gender_weight_2),dataframe=wapoll)

#NOT RUN: INCLUDE PARTY IN AGE*GENDER WEIGHT
party_tab2 <- svymean(~interaction(wapoll$pid), design=svyd_age_gender$survey_design, na.rm=TRUE)
weight_to_party <- weight_amount(weight_props_party,c(party_tab2[[1]]*100,party_tab2[[2]]*100,party_tab2[[3]]*100))
weight_party_2 <- variable_weight(wapoll$pid,weight_to_party)

#NOT RUN: WEIGHT CREATED FOR age*gender*party
svyd_age_gender_party <- survey_weight(cbind(svyd_age_gender$survey_weight,weight_party_2),dataframe=wapoll)

#NOT RUN: Region Proportions (weighted by (age*gender)*Party)
region_tab2 <- svymean(~interaction(wapoll$region), design=svyd_age_gender_party$survey_design, na.rm=TRUE)
#NOT RUN: INCLUDE REGION IN PARTY*AGE*GENDER WEIGHT
weight_to_region <- weight_amount(weight_props_region,c(region_tab2[[1]]*100,region_tab2[[2]]*100,region_tab2[[3]]*100))
weight_region_2 <- variable_weight(wapoll$region,weight_to_region)

#NOT RUN: CREATE INITIAL "FINAL" WEIGHT
svyd_age_gender_party_region <- survey_weight(cbind(svyd_age_gender_party$survey_weight,weight_region_2),dataframe=wapoll)

#NOT RUN: EXAMINE WEIGHTED TABS
age_tabs <- svymean(~interaction(wapoll$age3), design=svyd_age_gender_party_region$survey_design, na.rm=TRUE)
gender_tabs <- svymean(~interaction(wapoll$gender), design=svyd_age_gender_party_region$survey_design, na.rm=TRUE)
party_tabs <- svymean(~interaction(wapoll$pid), design=svyd_age_gender_party_region$survey_design, na.rm=TRUE)
region_tabs <- svymean(~interaction(wapoll$region), design=svyd_age_gender_party_region$survey_design, na.rm=TRUE)

#NOT RUN: PUT WEIGHT PROPORTIONS AND NEWLY CALCULATED WEIGHTED PROPORTIONS IN VECTORS AND SEND TO tab_look
weight_props <- c( weight_props_age, weight_props_gender, weight_props_party, weight_props_region)
weighted_data <- c( matrix(age_tabs)[,1]*100, matrix(gender_tabs)[,1]*100, matrix(party_tabs)[,1]*100, matrix(region_tabs)[,1]*100 )
tab_weights <- tab_look(weight_props, weighted_data)
tab_weights