cordata

This function calculates the correlation for the data and Cohen's d effect sizes, both based on pooled and on treatment standard deviations. It can optionally display the results in an HTML widget.

In repeated measures studies with extreme large or small values it is common
that the subjects measurements on average are closer to the mean of the basic population.
Interpreting possible changes in the mean in such situations can lead to biased results
since the values were not randomly selected, they come from truncated sampling.
This method allows to estimate the range of means where treatment effects are likely to occur
when regression toward the mean is present.
Ostermann, T., Willich, Stefan N. & Luedtke, Rainer. (2008). Regression toward the mean - a detection method for unknown population mean based on Mee and Chua's algorithm. BMC Medical Research Methodology.<doi:10.1186/1471-2288-8-52>.
Acknowledgments: We would like to acknowledge "Lena Roth" and "Nico Steckhan" for the package's initial updates (Q3 2024) and continued supervision and guidance. Both have contributed to discussing and integrating these methods into the package, ensuring they are up-to-date and contextually relevant.

Daniela Recchia

regtomean

Regression Toward the Mean

Thomas Ostermann

Julian Stein

cordata function

<dl> <dt>Before</dt>
<dd>a numeric vector giving the data values for the first (before) measure.</dd> <dt>After</dt>
<dd>a numeric vector giving the data values for the second (after) measure.</dd> <dt>within</dt>
<dd>A logical indicating whether the effect sizes should be computed based on paired samples (<code>TRUE</code>, default) or independent samples (<code>FALSE</code>).</dd> <dt>data</dt>
<dd>an optional data frame containing the variables in the formula. By <code>default</code> the variables are taken from <code>environment (formula)</code>.</dd></dl>

Arguments

Daniela Recchia, Thomas Ostermann.

Author

Correlation and Cohen's d effect sizes. — cordata

<dl>

 <dt>Before</dt>
<dd>a numeric vector giving the data values for the first (before) measure.</dd>

 <dt>After</dt>
<dd>a numeric vector giving the data values for the second (after) measure.</dd>

 <dt>within</dt>
<dd>A logical indicating whether the effect sizes should be computed based on paired samples (<code>TRUE</code>, default) or independent samples (<code>FALSE</code>).</dd>

 <dt>data</dt>
<dd>an optional data frame containing the variables in the formula. By <code>default</code> the variables are taken from <code>environment (formula)</code>.</dd>

</dl>

cordata: Correlation and Cohen's d effect sizes.

Description

Usage

Value

Arguments

Author

Details

References

See Also

Examples