psrsq

Compute the Nagelkerke and Cox--Snell pseudo-rsquared statistics, primarily for logistic regression. A generic function with methods for <code>glm</code> and <code>svyglm</code>. The method for <code>svyglm</code> objects uses the design-based estimators described by Lumley (2017)

regression

survey

Summary statistics, two-sample tests, rank tests, generalised linear models, cumulative link models, Cox models, loglinear models, and general maximum pseudolikelihood estimation for multistage stratified, cluster-sampled, unequally weighted survey samples. Variances by Taylor series linearisation or replicate weights. Post-stratification, calibration, and raking. Two-phase subsampling designs. Graphics. PPS sampling without replacement. Small-area estimation.

Thomas Lumley

Analysis of Complex Survey Samples

psrsq function

<dl> <dt>object</dt>
<dd>A regression model (<code>glm</code> or <code>svyglm</code>)</dd> <dt>method</dt>
<dd>Which statistic to compute</dd> <dt>...</dt>
<dd>For future expansion</dd></dl>

Arguments

Pseudo-Rsquareds — psrsq

<dl>

 <dt>object</dt>
<dd>A regression model (<code>glm</code> or <code>svyglm</code>)</dd>

 <dt>method</dt>
<dd>Which statistic to compute</dd>

 <dt>...</dt>
<dd>For future expansion</dd>

</dl>

psrsq: Pseudo-Rsquareds

Description

Usage

Value

Arguments

References

See Also

Examples