sampSurf (version 0.7-6)

monteNTSample-class: Class "monteNTSample"

Description

This class contains the necessary structure for doing normal theory sample size experiments under simple random sampling.

Objects from the Class

Objects can be created by calls of the form new("monteNTSample", ...). However, it is preferable to use the constructor method of the same name monteNTSample to minimize problems with potentially invalid objects.

Slots

Only one new slot is added here from the superclass. In addition, the definitions for three other slots that are method-dependent are also given.

t.values:

Object of class "numeric": Student's t values for each sample size n with two-tailed \(alpha\)-level alpha.

means:

Object of class "data.frame": The data frame contains the individual means for all mcSamples by length(n) samples drawn from the population. Taking column means gives the overall mean for each of the sample sizes.

lowerCIs:

Object of class "data.frame": This is the usual normal theory lower limit for each sample: \(\bar{y} - t^{1-\alpha/2}_{n-1} s_{\bar{y}}\), where \(t\) is Student's \(t\)-value and \(s_{\bar{y}}\) is the standard error of the mean for the sample.

upperCIs:

Object of class "data.frame": This is the usual normal theory upper limit for each sample: \(\bar{y} + t^{1-\alpha/2}_{n-1} s_{\bar{y}}\), where \(t\) is Student's \(t\)-value and \(s_{\bar{y}}\) is the standard error of the mean for the sample. object.

Extends

Class "'>monteSample", directly. Class "'>monteNTSampleOrNULL", directly.

Methods

No methods defined with class "monteNTSample" in the signature.

References

The ‘“monte”: When is n Sufficiently Large?’ vignette.

See Also

'>monte, '>montePop

Examples

# NOT RUN {
showClass("monteNTSample")
# }