svyttest

confint.svyttest

One-sample or two-sample t-test. This function is a wrapper for
<code>svymean</code> in the one-sample case and for
<code>svyglm</code> in the two-sample case. Degrees of freedom are
<code>degf(design)-1</code> for the one-sample test and <code>degf(design)-2</code>
for the two-sample case.

htest

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

svyttest function

<dl> <dt>formula</dt>
<dd>Formula, <code>outcome~group</code> for two-sample,
 <code>outcome~0</code> or <code>outcome~1</code> for one-sample. The <code>group</code> variable 
 must be a factor or character with two levels, or be coded 0/1 or 1/2</dd> <dt>design</dt>
<dd>survey design object</dd> <dt>...</dt>
<dd>for methods</dd></dl>

Arguments

Design-based t-test — svyttest

<dl>

 <dt>formula</dt>
<dd>Formula, <code>outcome~group</code> for two-sample,
 <code>outcome~0</code> or <code>outcome~1</code> for one-sample. The <code>group</code> variable 
 must be a factor or character with two levels, or be coded 0/1 or 1/2</dd>

 <dt>design</dt>
<dd>survey design object</dd>

 <dt>...</dt>
<dd>for methods</dd>

</dl>

svyttest: Design-based t-test

Description

Usage

Value

Arguments

See Also

Examples