<p>The <code>lep</code> data frame has 1370 rows and 7 columns. This was an
unmatched case-control study in which incident cases of leprosy in a
region of N. Malawi were compared with population controls.</p>

datasets

Functions for demographic and epidemiological analysis in
the Lexis diagram, i.e. register and cohort follow-up data. In
particular representation, manipulation, rate estimation and
simulation for multistate data - the Lexis suite of functions, which
includes interfaces to 'mstate', 'etm' and 'cmprsk' packages.
Contains functions for Age-Period-Cohort and Lee-Carter modeling and
a function for interval censored data. Has functions for extracting
and manipulating parameter estimates and predicted values (ci.lin
and its cousins), as well as a number of epidemiological data sets.

Bendix Carstensen

Statistical Analysis in Epidemiology

Martyn Plummer

Esa Laara

Michael Hills

lep function

<p>This data frame contains the following columns:</p><table class="table">
<tr><td><code>id</code>:</td><td>subject identifier: a numeric vector</td></tr>
<tr><td><code>d</code>:</td><td>case/control status: a numeric vector (1=case, 0=control)</td></tr>
<tr><td><code>age</code>:</td><td>a factor with levels
<code>5-9</code> 
<code>10-14</code> 
<code>15-19</code> 
<code>20-24</code> 
<code>25-29</code> 
<code>30-44</code> 
<code>45+</code></td></tr>
<tr><td><code>sex</code>:</td><td>a factor with levels
<code>male</code>,  
<code>female</code></td></tr>
<tr><td><code>bcg</code>:</td><td>presence of vaccine scar, a factor with levels
<code>no</code> 
<code>yes</code></td></tr>
<tr><td><code>school</code>:</td><td>schooling, a factor with levels
<code>none</code> 
<code>1-5yrs</code> 
<code>6-8yrs</code> 
<code>sec/tert</code></td></tr>
<tr><td><code>house</code>:</td><td>housing, a factor with levels
<code>brick</code> 
<code>sunbrick</code> 
<code>wattle</code> 
<code>temp</code></td></tr>
</table><p></p><p></p>

Format

An unmatched case-control study of leprosy incidence — lep

<p>This data frame contains the following columns:</p><table class='table'>
<tr><td><code>id</code>:</td><td>subject identifier: a numeric vector</td></tr>
<tr><td><code>d</code>:</td><td>case/control status: a numeric vector (1=case, 0=control)</td></tr>
<tr><td><code>age</code>:</td><td>a factor with levels
<code>5-9</code> 
<code>10-14</code> 
<code>15-19</code> 
<code>20-24</code> 
<code>25-29</code> 
<code>30-44</code> 
<code>45+</code></td></tr>
<tr><td><code>sex</code>:</td><td>a factor with levels
<code>male</code>,  
<code>female</code></td></tr>
<tr><td><code>bcg</code>:</td><td>presence of vaccine scar, a factor with levels
<code>no</code> 
<code>yes</code></td></tr>
<tr><td><code>school</code>:</td><td>schooling, a factor with levels
<code>none</code> 
<code>1-5yrs</code> 
<code>6-8yrs</code> 
<code>sec/tert</code></td></tr>
<tr><td><code>house</code>:</td><td>housing, a factor with levels
<code>brick</code> 
<code>sunbrick</code> 
<code>wattle</code> 
<code>temp</code></td></tr>
</table>



`id`:	subject identifier: a numeric vector
`d`:	case/control status: a numeric vector (1=case, 0=control)
`age`:	a factor with levels `5-9` `10-14` `15-19` `20-24` `25-29` `30-44` `45+`
`sex`:	a factor with levels `male`, `female`
`bcg`:	presence of vaccine scar, a factor with levels `no` `yes`
`school`:	schooling, a factor with levels `none` `1-5yrs` `6-8yrs` `sec/tert`
`house`:	housing, a factor with levels `brick` `sunbrick` `wattle` `temp`

lep: An unmatched case-control study of leprosy incidence

Description

Arguments

Format

Examples