SimTestDiff
(Package: SimComp) :
Simultaneous Tests for Differences of Means of Multiple Endpoints
Simultaneous tests for general contrasts (linear functions) of normal means (e.g., "Dunnett", "Tukey", "Williams" ect.) when there is more than one primary response variable (endpoint). The procedure of Hasler and Hothorn (2011) is applied for differences of means of normally distributed data. The covariance matrices (containing the covariances between the endpoints) may be assumed to be equal or possibly unequal for the different groups (Hasler, 2014). For the case of only a single endpoint and unequal covariance matrices (variances), the procedure coincides with the PI procedure of Hasler and Hothorn (2008).
SimCiDiff
(Package: SimComp) :
Simultaneous Confidence Intervals for Differences of Means of Multiple Endpoints
Simultaneous confidence intervals for general contrasts (linear functions) of normal means (e.g., "Dunnett", "Tukey", "Williams" ect.) when there is more than one primary response variable (endpoint). The procedure of Hasler and Hothorn (2011) is applied for differences of means of normally distributed data. The covariance matrices (containing the covariances between the endpoints) may be assumed to be equal or possibly unequal for the different groups (Hasler, 2014). For the case of only a single endpoint and unequal covariance matrices (variances), the procedure coincides with the PI procedure of Hasler and Hothorn (2008).
SimCiRat
(Package: SimComp) :
Simultaneous Confidence Intervals for Ratios of Means of Multiple Endpoints
Simultaneous confidence intervals for ratios of contrasts (linear functions) of normal means (e.g., "Dunnett", "Tukey", "Williams" ect.) when there is more than one primary response variable (endpoint). The procedure of Hasler and Hothorn (2012) is applied for ratios of means of normally distributed data. The covariance matrices (containing the covariances between the endpoints) may be assumed to be equal or possibly unequal for the different groups (Hasler, 2014). For the case of only a single endpoint and unequal covariance matrices (variances), the procedure coincides with the PI procedure of Hasler and Hothorn (2008).
ermvnorm
(Package: SimComp) :
Multivariate Normal Random Numbers with Exact Parameters
Random numbers of the multivariate normal distribution with EXACT mean vector, EXACT variance vector and approximate correlation matrix. This function is based on the function rmvnorm of the package mvtnorm.
● Data Source:
CranContrib
● Keywords: datagen, distribution
● Alias: ermvnorm
●
3 images
SimTestRat
(Package: SimComp) :
Simultaneous Tests for Ratios of Means of Multiple Endpoints
Simultaneous tests for ratios of contrasts (linear functions) of normal means (e.g., "Dunnett", "Tukey", "Williams" ect.) when there is more than one primary response variable (endpoint). The procedure of Hasler and Hothorn (2012) is applied for ratios of means of normally distributed data. The covariance matrices (containing the covariances between the endpoints) may be assumed to be equal or possibly unequal for the different groups (Hasler, 2014). For the case of only a single endpoint and unequal covariance matrices (variances), the procedure coincides with the PI procedure of Hasler and Hothorn (2008).
DfSattRat
(Package: SimComp) :
Degrees of Freedom Accoding to Satterthwaite (1946) for Ratios of Means
Degrees of freedom accoding to Satterthwaite (1946) for (multivariate) t-distributions related to multiple contrast tests or corresponding simultaneous confidence intervals for ratios of means.
providing 
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