Stata 15 help for pwmean

[R] pwmean -- Pairwise comparisons of means

Syntax

pwmean varname, over(varlist) [options]

options Description ------------------------------------------------------------------------- Main * over(varlist) compare means across each combination of the levels in varlist mcompare(method) adjust for multiple comparisons; default is mcompare(noadjust)

Reporting level(#) confidence level; default is level(95) cieffects display a table of mean differences and confidence intervals; the default pveffects display a table of mean differences and p-values effects display a table of mean differences with p-values and confidence intervals cimeans display a table of means and confidence intervals groups display a table of means with codes that group them with other means that are not significantly different sort sort results tables by displayed mean or difference display_options control column formats, line width, and factor-variable labeling ------------------------------------------------------------------------- *over(varlist) is required. See [R] pwmean postestimation for features available after estimation.

method Description ------------------------------------------------------------------------- noadjust do not adjust for multiple comparisons; the default bonferroni Bonferroni's method sidak Sidak's method scheffe Scheffe's method tukey Tukey's method snk Student-Newman-Keuls's method duncan Duncan's method dunnett Dunnett's method -------------------------------------------------------------------------

Menu

Statistics > Summaries, tables, and tests > Summary and descriptive statistics > Pairwise comparisons of means

Description

pwmean performs pairwise comparisons of means. It computes all pairwise differences of the means of varname over the combination of the levels of the variables in varlist. The tests and confidence intervals for the pairwise comparisons assume equal variances across groups. pwmean also allows for adjusting the confidence intervals and p-values to account for multiple comparisons using Bonferroni's method, Scheffe's method, Tukey's method, Dunnett's method, and others.

See [R] pwcompare for performing pairwise comparisons of means, estimated marginal means, and other types of marginal linear predictions after anova, regress, and most other estimation commands.

Options

+------+ ----+ Main +-------------------------------------------------------------

over(varlist) is required and specifies that the means are computed for each combination of the levels of the variables in varlist.

mcompare(method) specifies the method for computing p-values and confidence intervals that account for multiple comparisons.

Most methods adjust the comparisonwise error rate, alpha_c, to achieve a prespecified experimentwise error rate, alpha_e.

mcompare(noadjust) is the default; it specifies no adjustment.

alpha_c = alpha_e

mcompare(bonferroni) adjusts the comparisonwise error rate based on the upper limit of the Bonferroni inequality:

alpha_e <= m * alpha_c

where m is the number of comparisons within the term.

The adjusted comparisonwise error rate is

alpha_c = alpha_e/m

mcompare(sidak) adjusts the comparisonwise error rate based on the upper limit of the probability inequality

alpha_e <= 1 - (1 - alpha_c)^m

where m is the number of comparisons within the term.

The adjusted comparisonwise error rate is

alpha_c = 1 - (1 - alpha_e)^(1/m)

This adjustment is exact when the m comparisons are independent.

mcompare(scheffe) controls the experimentwise error rate using the F (or chi-squared) distribution with degrees of freedom equal to k-1 where k is the number of means being compared.

mcompare(tukey) uses what is commonly referred to as Tukey's honestly significant difference. This method uses the Studentized range distribution instead of the t distribution.

mcompare(snk) is a variation on mcompare(tukey) that counts only the number of means participating in the range for a given comparison instead of the full number of means.

mcompare(duncan) is a variation on mcompare(snk) with additional adjustment to the significance probabilities.

mcompare(dunnett) uses Dunnett's method for making comparisons with a reference category.

+-----------+ ----+ Reporting +--------------------------------------------------------

level(#) specifies the confidence level, as a percentage, for confidence intervals. The default is level(95) or as set by set level. The significance level used by the groups option is 100-#, expressed as a percentage.

cieffects specifies that a table of the pairwise comparisons of means with their standard errors and confidence intervals be reported. This is the default.

pveffects specifies that a table of the pairwise comparisons of means with their standard errors, test statistics, and p-values be reported.

effects specifies that a table of the pairwise comparisons of means with their standard errors, test statistics, p-values, and confidence intervals be reported.

cimeans specifies that a table of the means with their standard errors and confidence intervals be reported.

groups specifies that a table of the means with their standard errors and group codes be reported. Means with the same letter in the group code are not significantly different at the specified significance level.

sort specifies that the reported tables be sorted by the mean or difference that is displayed in the table.

display_options: nofvlabel, fvwrap(#), fvwrapon(style), cformat(%fmt), pformat(%fmt), sformat(%fmt), and nolstretch.

nofvlabel displays factor-variable level values rather than attached value labels. This option overrides the fvlabel setting; see [R] set showbaselevels.

fvwrap(#) specifies how many lines to allow when long value labels must be wrapped. Labels requiring more than # lines are truncated. This option overrides the fvwrap setting; see [R] set showbaselevels.

fvwrapon(style) specifies whether value labels that wrap will break at word boundaries or break based on available space.

fvwrapon(word), the default, specifies that value labels break at word boundaries.

fvwrapon(width) specifies that value labels break based on available space.

This option overrides the fvwrapon setting; see [R] set showbaselevels.

cformat(%fmt) specifies how to format means, standard errors, and confidence limits in the table of pairwise comparison of means.

pformat(%fmt) specifies how to format p-values in the table of pairwise comparison of means.

sformat(%fmt) specifies how to format test statistics in the table of pairwise comparison of means.

nolstretch specifies that the width of the table of pairwise comparisons not be automatically widened to accommodate longer variable names. The default, lstretch, is to automatically widen the table of pairwise comparisons up to the width of the Results window. To change the default, use set lstretch off. nolstretch is not shown in the dialog box.

Examples

Setup . webuse yield

Mean yield for each fertilizer . pwmean yield, over(fertilizer) cimeans

Pairwise comparisons of mean yields for the fertilizers . pwmean yield, over(fertilizer) effects

Pairwise comparisons of the mean yields using Tukey's adjustment for multiple comparisons when computing p-values . pwmean yield, over(fertilizer) pveffects mcompare(tukey)

Comparisons of the mean yield for each fertilizer to the control (fertilizer 1) using Dunnett's adjustment . pwmean yield, over(fertilizer) effects mcompare(dunnett)

Stored results

pwmean stores the following in e():

Scalars e(df_r) variance degrees of freedom e(balanced) 1 if fully balanced data, 0 otherwise

Macros e(cmd) pwmean e(cmdline) command as typed e(title) title in output e(depvar) name of variable from which the means are computed e(over) varlist from over() e(properties) b V

Matrices e(b) mean estimates e(V) variance-covariance matrix of the mean estimates e(error) mean estimability codes; 0 means estimable, 8 means not estimable e(b_vs) mean difference estimates e(V_vs) variance-covariance matrix of the mean difference estimates e(error_vs) mean difference estimability codes; 0 means estimable, 8 means not estimable


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