osteoarthritis

<code>osteoarthritis</code> includes demographic data of 2,585 units (individuals) with or at risk of knee osteoarthritis. The recorded data has missing values in body mass index (<code>BMI</code>, a quantitative variable), race (<code>RAC</code>, a categorical qualitative variable), smoking status (<code>SMK</code>, a binary qualitative variable), osteoporosis status at baseline (<code>OSP</code>, a binary qualitative variable), and knee osteoarthritis status at follow-up (<code>KOA</code>, a binary qualitative variable).

datasets

Provides the necessary tools for the pre-processing techniques of matching and weighting multiply imputed datasets to control for effects of confounders and to reduce the degree of dependence on certain modeling assumptions in studying the causal associations between an exposure and an outcome. This package includes functions to perform matching within and across the multiply imputed datasets using several matching methods, to estimate weights of units in the imputed datasets using several weighting methods, to calculate the causal effect estimate in each matched or weighted dataset using parametric or non-parametric statistical models, and to pool the obtained estimates from these models according to Rubin's rules (please see <https://github.com/FarhadPishgar/MatchThem> for details).

Farhad Pishgar

MatchThem

Matching and Weighting Multiply Imputed Datasets

Noah Greifer

Cl<c3><a9>mence Leyrat

osteoarthritis function

This dataset contains 2,585 rows and 7 columns. Each row presents data of an unit (individual) and each column presents data of a characteristics of that individual. The columns are:<dl class="dl-horizontal">
 <dt>AGE</dt><dd>Age of each unit (individual);</dd>
 <dt>SEX</dt><dd>Gender of each unit (individual), coded as <code>0</code> (female) and <code>1</code> (male);</dd>
 <dt>BMI</dt><dd>Estimated body mass index of each unit (individual);</dd>
 <dt>RAC</dt><dd>Race of each unit (individual), coded as <code>0</code> (other), <code>1</code> (caucasian), <code>2</code> (african american), and <code>3</code> (asian);</dd>
 <dt>SMK</dt><dd>The smoking status of each unit, coded as <code>0</code> (non-smoker) and <code>1</code> (smoker);</dd>
 <dt>OSP</dt><dd>Osteoporosis status of each unit (individual) at baseline, coded as <code>0</code> (negative) and <code>1</code> (positive); and</dd>
 <dt>KOA</dt><dd>Knee osteoarthritis status of each unit (individual) in the follow-up, coded as <code>0</code> (at risk) and <code>1</code> (diagnosed).</dd>
</dl>

Format

Data of 2,585 Participants in the OAI Project — osteoarthritis

This dataset contains 2,585 rows and 7 columns. Each row presents data of an unit (individual) and each column presents data of a characteristics of that individual. The columns are:<dl class='dl-horizontal'>
 <dt>AGE</dt><dd>Age of each unit (individual);</dd>
 <dt>SEX</dt><dd>Gender of each unit (individual), coded as <code>0</code> (female) and <code>1</code> (male);</dd>
 <dt>BMI</dt><dd>Estimated body mass index of each unit (individual);</dd>
 <dt>RAC</dt><dd>Race of each unit (individual), coded as <code>0</code> (other), <code>1</code> (caucasian), <code>2</code> (african american), and <code>3</code> (asian);</dd>
 <dt>SMK</dt><dd>The smoking status of each unit, coded as <code>0</code> (non-smoker) and <code>1</code> (smoker);</dd>
 <dt>OSP</dt><dd>Osteoporosis status of each unit (individual) at baseline, coded as <code>0</code> (negative) and <code>1</code> (positive); and</dd>
 <dt>KOA</dt><dd>Knee osteoarthritis status of each unit (individual) in the follow-up, coded as <code>0</code> (at risk) and <code>1</code> (diagnosed).</dd>
</dl>

osteoarthritis: Data of 2,585 Participants in the OAI Project

Description

Usage

Arguments

Format