ihd_mar

This dataset is a subset from the India Human Development survey. This dataset is included in the package only for demonstration purposes and should not be used for other purposes.

datasets

Implements a new multiple imputation method that draws
imputations from a latent joint multivariate normal model which
underpins generally structured data. This model is constructed using a
sequence of flexible conditional linear models that enables the
resulting procedure to be efficiently implemented on high dimensional
datasets in practice. See Robbins (2021) <arXiv:2008.02243>.

Michael Robbins

gerbil

Generalized Efficient Regression-Based Imputation with Latent
Processes

Max Griswold

Pedro Nascimento de Lima

ihd_mar function

A data frame with 42155 rows and 8 variables:<dl>
	<dt>sex</dt>
<dd>1 = individual is male; 2 = individual is female</dd>	<dt>age</dt>
<dd>Age of the individual, between 0 &amp; 99</dd>	<dt>marital_status</dt>
<dd>Individual’s marital status. 0 = married, absent spouse, 1 = Married, 2 = Unmarried, 3 = Widowed, 4 = Divorced/Separated, 5 = married, no gauna</dd>	<dt>job_field</dt>
<dd>Refer’s to the field of the individual’s profession or job status (i.e. agricultural worker; small business owner; student; unemployed; etc.</dd>	<dt>farm_labour_days</dt>
<dd>Number of days a year the individual worked on a farm. Can take on the value zero</dd>	<dt>own_livestock</dt>
<dd>0 = Individual does not own livestock. 1 = Individual does own livestock</dd>	<dt>education_level</dt>
<dd>Years of schooling attained by the individual. Censored for values above 16.</dd>	<dt>income</dt>
<dd>Household’s income, in rupees. Value can be negative</dd>
</dl>

Format

Missing at Random example data from the India Human Development Survey — ihd_mar

A data frame with 42155 rows and 8 variables:<dl>
	<dt>sex</dt>
<dd>1 = individual is male; 2 = individual is female</dd>

	<dt>age</dt>
<dd>Age of the individual, between 0 &amp; 99</dd>

	<dt>marital_status</dt>
<dd>Individual’s marital status. 0 = married, absent spouse, 1 = Married, 2 = Unmarried, 3 = Widowed, 4 = Divorced/Separated, 5 = married, no gauna</dd>

	<dt>job_field</dt>
<dd>Refer’s to the field of the individual’s profession or job status (i.e. agricultural worker; small business owner; student; unemployed; etc.</dd>

	<dt>farm_labour_days</dt>
<dd>Number of days a year the individual worked on a farm. Can take on the value zero</dd>

	<dt>own_livestock</dt>
<dd>0 = Individual does not own livestock. 1 = Individual does own livestock</dd>

	<dt>education_level</dt>
<dd>Years of schooling attained by the individual. Censored for values above 16.</dd>

	<dt>income</dt>
<dd>Household’s income, in rupees. Value can be negative</dd>


</dl>

ihd_mar: Missing at Random example data from the India Human Development Survey

Description

Usage

Arguments

Format