Description Objects from the Class Slots Extends Methods Author(s) References See Also Examples

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

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.

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-α/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-α/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.

Class `"monteSample"`

, directly.

Class `"monteNTSampleOrNULL"`

, directly.

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

Jeffrey H. Gove

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

1 | ```
showClass("monteNTSample")
``` |

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