ss16pusa_sample_zeros_miss: Example dataframe for input categorical data with structural...

In NPBayesImputeCat: Non-Parametric Bayesian Multiple Imputation for Categorical Data

Example dataframe for input categorical data with structural zeros (with missing values).

Description

Example dataframe for input categorical data with structural zeros (with missing values). It contains 1000 observations and 5 variables.

[,1]	AGEP	age	7 levels: 16; 17; [18, 24]; [25, 35]; [36, 50]; [51, 70]; (70, ).
[,2]	MAR	marital status	5 levels: Married; Widowed; Divorced; Separated;
			Never married.
[,3]	SCHL	educational attainment	9 levels: Up to K0; Some K12, no diploma;
			High school diploma or GED; Some college, no degree;
			Associate's degree; Bachelor's degree; Master's degree;
			Professional degree; Doctorate degree.
[,4]	SEX	sex	2 levels: Male; Female.
[,5]	WKL	When last worked	3 levels: Within the last 12 months; 1-5 years ago;
			Over 5 years ago or never worked.

NPBayesImputeCat documentation built on Oct. 3, 2022, 5:05 p.m.