ANOVA.Tests: ANOVA tests for each column of a continuous data Matrix.
In villardon/MultBiplotRGUI: Graphical User Interface for MultBiplotR
Description
Usage
Arguments
Details
Value
Author(s)
References
See Also
Examples
Description
ANOVA tests for each column of a continuous data Matrix.
Usage
1
ANOVA.Tests(X, groups, posthoc = "none", alternative = "two.sided", digits = 4, UnequalVar = TRUE)
Arguments
X
The data matrix. Each column will be analyzed separately.
groups
A factor containing the groups to compare
posthoc
Post-Hoc Tests for the Anova (used by pairwise t tests). Must be a subset of ("holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none")
alternative
Alternative hypothesis for the pairwise t tests ("two.sided", "less", "greater"))
digits
Number of decimal digits for the results
UnequalVar
Logical to indicate if the results for unequal variances should also be included.
Details
One way Analysis of Variance for the columns of a data matrix.
Value
A list
Author(s)
Jose Luis Vicente villardon
References
Benjamini, Y., and Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society Series B 57, 289–300.
Benjamini, Y., and Yekutieli, D. (2001). The control of the false discovery rate in multiple testing under dependency. Annals of Statistics 29, 1165–1188.
Holm, S. (1979). A simple sequentially rejective multiple test procedure. Scandinavian Journal of Statistics 6, 65–70.
Hommel, G. (1988). A stagewise rejective multiple test procedure based on a modified Bonferroni test. Biometrika 75, 383–386.
Hochberg, Y. (1988). A sharper Bonferroni procedure for multiple tests of significance. Biometrika 75, 800–803.
Shaffer, J. P. (1995). Multiple hypothesis testing. Annual Review of Psychology 46, 561–576. (An excellent review of the area.)
Sarkar, S. (1998). Some probability inequalities for ordered MTP2 random variables: a proof of Simes conjecture. Annals of Statistics 26, 494–504.
Sarkar, S., and Chang, C. K. (1997). Simes' method for multiple hypothesis testing with positively dependent test statistics. Journal of the American Statistical Association 92, 1601–1608.
Wright, S. P. (1992). Adjusted P-values for simultaneous inference. Biometrics 48, 1005–1013. (Explains the adjusted P-value approach.)
See Also
Examples
1
2
3
data(iris)
txt=ANOVA.Tests(iris[,1:4], groups=iris[,5])
GeneralResults(title="Analysis of Variance", text=txt)
villardon/MultBiplotRGUI documentation built on May 12, 2019, 2:03 p.m.
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Description Usage Arguments Details Value Author(s) References See Also Examples
Description
ANOVA tests for each column of a continuous data Matrix.
Usage
1 | ANOVA.Tests(X, groups, posthoc = "none", alternative = "two.sided", digits = 4, UnequalVar = TRUE)
|
Arguments
X |
The data matrix. Each column will be analyzed separately. |
groups |
A factor containing the groups to compare |
posthoc |
Post-Hoc Tests for the Anova (used by pairwise t tests). Must be a subset of ("holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none") |
alternative |
Alternative hypothesis for the pairwise t tests ("two.sided", "less", "greater")) |
digits |
Number of decimal digits for the results |
UnequalVar |
Logical to indicate if the results for unequal variances should also be included. |
Details
One way Analysis of Variance for the columns of a data matrix.
Value
A list
Author(s)
Jose Luis Vicente villardon
References
Benjamini, Y., and Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society Series B 57, 289–300.
Benjamini, Y., and Yekutieli, D. (2001). The control of the false discovery rate in multiple testing under dependency. Annals of Statistics 29, 1165–1188.
Holm, S. (1979). A simple sequentially rejective multiple test procedure. Scandinavian Journal of Statistics 6, 65–70.
Hommel, G. (1988). A stagewise rejective multiple test procedure based on a modified Bonferroni test. Biometrika 75, 383–386.
Hochberg, Y. (1988). A sharper Bonferroni procedure for multiple tests of significance. Biometrika 75, 800–803.
Shaffer, J. P. (1995). Multiple hypothesis testing. Annual Review of Psychology 46, 561–576. (An excellent review of the area.)
Sarkar, S. (1998). Some probability inequalities for ordered MTP2 random variables: a proof of Simes conjecture. Annals of Statistics 26, 494–504.
Sarkar, S., and Chang, C. K. (1997). Simes' method for multiple hypothesis testing with positively dependent test statistics. Journal of the American Statistical Association 92, 1601–1608.
Wright, S. P. (1992). Adjusted P-values for simultaneous inference. Biometrics 48, 1005–1013. (Explains the adjusted P-value approach.)
See Also
Examples
1 2 3 | data(iris)
txt=ANOVA.Tests(iris[,1:4], groups=iris[,5])
GeneralResults(title="Analysis of Variance", text=txt)
|
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