employee

A dataset with information on background characteristics and salary of 473 employees.

datasets

Regression trunk model estimation proposed by Dusseldorp and Meulman (2004) <doi:10.1007/bf02295641> and Dusseldorp, Conversano, Van Os (2010) <doi:10.1198/jcgs.2010.06089>, integrating a regression tree and a multiple regression model.

Elise Dusseldorp

stima

Simultaneous Threshold Interaction Modeling Algorithm

Claudio Conversano

Cor Ninaber

Kristof Meers

Peter Neufeglise

Juan Claramunt

employee function

A data frame with 473 observations on the following 9 variables:<dl>
 <dt><code>salary</code></dt>
<dd>a numeric variable, used as response variable: current salary in US dollars</dd> <dt><code>age</code></dt>
<dd>a numeric variable: age in years</dd> <dt><code>edu</code></dt>
<dd>a numeric variable: educational level in years</dd> <dt><code>startsal</code></dt>
<dd>a numeric variable: beginning salary in US dollars</dd> <dt><code>jobtime</code></dt>
<dd>a numeric variable: months since hire</dd> <dt><code>prevexp</code></dt>
<dd>a numeric variable: previous work experience in months</dd> <dt><code>minority</code></dt>
<dd>a factor variable: minority classification with levels <code>min</code>, indicating minority, and <code>no_min</code>, no minority</dd> <dt><code>gender</code></dt>
<dd>a factor variable: gender type with levels <code>f</code>, indicating female, and <code>m</code>, indicating male</dd> <dt><code>jobcat</code></dt>
<dd>a factor variable: type of job with levels <code>Clerical</code>, <code>Custodial</code>, and <code>manager</code></dd> 
</dl>

Format

Employee Dataset — employee

A data frame with 473 observations on the following 9 variables:<dl>
 <dt><code>salary</code></dt>
<dd>a numeric variable, used as response variable: current salary in US dollars</dd>

 <dt><code>age</code></dt>
<dd>a numeric variable: age in years</dd>

 <dt><code>edu</code></dt>
<dd>a numeric variable: educational level in years</dd>

 <dt><code>startsal</code></dt>
<dd>a numeric variable: beginning salary in US dollars</dd>

 <dt><code>jobtime</code></dt>
<dd>a numeric variable: months since hire</dd>

 <dt><code>prevexp</code></dt>
<dd>a numeric variable: previous work experience in months</dd>

 <dt><code>minority</code></dt>
<dd>a factor variable: minority classification with levels <code>min</code>, indicating minority, and <code>no_min</code>, no minority</dd>

 <dt><code>gender</code></dt>
<dd>a factor variable: gender type with levels <code>f</code>, indicating female, and <code>m</code>, indicating male</dd>

 <dt><code>jobcat</code></dt>
<dd>a factor variable: type of job with levels <code>Clerical</code>, <code>Custodial</code>, and <code>manager</code></dd>

 
</dl>

employee: Employee Dataset

Description

Usage

Arguments

Format

References