Анализ множественного ответа

df1=data.frame(c("male","female","male"),c("1","2","3","4","5","6"),seq(141,170))
names(df1) = c("gender","age","height")
df1$age <- factor(df1$age,
levels=c(1,2,3,4,5,6),
labels=c("16-24","25-34","35-44","45-54","55-64","65+"))
q1a=c(1,0,1,0,0,1);q1b=c(0,0,2,2,2,0);q1c=c(0,0,3,3,0,3) #1,2 and 3 used to be compatible with existing datasets. Could change all to 1 if necessary.
df2=data.frame(q1a=q1a,q1b=q1b,q1c=q1c); df1 <- cbind(df1,df2)

rm(q1a,q1b,q1c,df2)

Я хочу воспроизвести анализ вопросов с множественными ответами из SPSS в R.

В настоящее время я использую этот код :

#creating function for analysing questions with grouped data 
multfreqtable <- function(a, b, c){

# number of respondents (for percent of cases)
totrep=sum(a==1|b==2|c==3) 

#creating frequency table
table_a=data.frame("a",sum(a==1))
names(table_a)=c("question","freq")
table_b=data.frame("b",sum(b==2))
names(table_b)=c("question","freq") 
table_c=data.frame("c",sum(c==3))
names(table_c)=c("question","freq")
table_question <-rbind(table_a,table_b,table_c)

#remove individual question tables
rm(table_a,table_b,table_c)

#adding total
total=as.data.frame("Total")
totalsum=(sum(table_question$freq,na.rm=TRUE))
totalrow=cbind(total,totalsum)
names(totalrow)=c("question","freq")
table_question=rbind(table_question,totalrow)

#adding percentage column to frequency table
percentcalc=as.numeric(table_question$freq)
percent=(percentcalc/totalsum)*100
table_question<-cbind(table_question,percent)

#adding percent of cases column to frequency table
poccalc=as.numeric(table_question$freq)
percentofcases=(poccalc/totrep)*100
table_question<-cbind(table_question,percentofcases)

#print percent of cases value
total_respondents <<- data.frame(totrep)

#remove all unnecessary data and values
rm(total,totalsum,totalrow,b,c,percent,percentcalc,percentofcases,totrep,poccalc)

return(table_question)
}

#calling function - must tie to data.frame using $ !!!
q1_frequency<-multfreqtable(df1$q1a,df1$q1b,df1$q1c)

#renaming percent of cases - This is very important while using current method
total_respondents_q1 <- total_respondents
rm(total_respondents)

Создание этой таблицы в результате:

Я ищу более эффективный способ сделать это, который в идеале не требовал бы редактирования функции, если бы были вопросы с более или менее множественным выбором.