predict.lsm

A fitted object of class <code>lsm</code>.

object

Optionally, a data frame in which to look for variables with which to predict. 
If omitted, the fitted linear predictors are used.

newdata

The type of prediction required. The default is on the scale of the linear predictors. 
The alternative <code>response</code> gives the predicted probabilities.

type

interval

level

further arguments passed to or from other methods.

Obtains predictions from a fitted <code>lsm</code> object.

When the values of the outcome variable Y are either 0 or 1,
the function lsm() calculates the estimation of the log likelihood
in the saturated model.
This model is characterized by Llinas (2006, ISSN:2389-8976) in section 2.3
through the assumptions 1 and 2.
The function LogLik() works (almost perfectly) when the number of independent
variables K is high, but for small K it calculates wrong values in some cases.
For this reason, when Y is dichotomous and the data are grouped in J populations,
it is recommended to use the function lsm() because it works very well for all K.

Jorge Villalba

Estimation of the log Likelihood of the Saturated Model

Humberto Llinas

Omar Fabregas

predict.lsm function

<dl><dt>object</dt>
<dd>A fitted object of class <code>lsm</code>.</dd>
<dt>newdata</dt>
<dd>Optionally, a data frame in which to look for variables with which to predict. 
If omitted, the fitted linear predictors are used.</dd>
<dt>type</dt>
<dd>The type of prediction required. The default is on the scale of the linear predictors. 
The alternative <code>response</code> gives the predicted probabilities.</dd>
<dt>interval</dt>
<dd>gives the</dd>
<dt>level</dt>
<dd>gives the</dd>
<dt>...</dt>
<dd>further arguments passed to or from other methods.</dd></dl>

Arguments

Predict  Method for lsm  Objects — predict.lsm

<dl>

<dt>object</dt>
<dd>A fitted object of class <code>lsm</code>.</dd>


<dt>newdata</dt>
<dd>Optionally, a data frame in which to look for variables with which to predict. 
If omitted, the fitted linear predictors are used.</dd>


<dt>type</dt>
<dd>The type of prediction required. The default is on the scale of the linear predictors. 
The alternative <code>response</code> gives the predicted probabilities.</dd>


<dt>interval</dt>
<dd>gives the</dd>


<dt>level</dt>
<dd>gives the</dd>


<dt>...</dt>
<dd>further arguments passed to or from other methods.</dd>

</dl>

predict.lsm: Predict Method for `lsm` Objects

Description

Usage

Value

Arguments

Details