{smcl} {hline} {cmd:help metaparm_content_opts}{right:(Roger Newson)} {hline} {title:Output-content options for {helpb metaparm}} {title:Syntax} {synoptset 28} {synopthdr} {synoptline} {synopt:{cmd:by(}{varlist}{cmd:)}}Variables specifying by-groups{p_end} {synopt:{cmdab:su:mvar}{cmd:(}{varlist}{cmd:)}}Variables to be summed in output dataset{p_end} {synopt:{opt dfc:ombine(combination_rule)}}Rule for combining degrees of freedom{p_end} {synopt:{opt idn:um(#)}}Value of numeric dataset ID variable{p_end} {synopt:{cmdab:nidn:um}{cmd:(}{help newvar:{it:newvarname}}{cmd:)}}Name of numeric dataset ID variable{p_end} {synopt:{opt ids:tr(string)}}Value of string dataset ID variable{p_end} {synopt:{cmdab:nids:tr}{cmd:(}{help newvar:{it:newvarname}}{cmd:)}}Name of string dataset ID variable{p_end} {synopt:{opt fo:rmat(formatting_list)}}Display formats for variables in the output dataset{p_end} {synoptline} {pstd} where {it:combination_rule} is {pstd} {cmdab:s:atterthwaite} | {cmdab:w:elch} | {cmdab:c:onstant} {pstd} and {it:formatting_list} is a list of form {pstd} {it:{help varlist:varlist_1} {help format:format_1} ... {help varlist:varlist_n} {help format:format_n}} {title:Description} {pstd} These options are available for {helpb metaparm} but not for {helpb parmcip}. They control the contents of the output dataset (or resultsset) created by {helpb metaparm}. {title:Options} {p 4 8 2} {cmd:by(}{varlist}{cmd:)} specifies a list of existing by-variables in the input dataset. {helpb metaparm} creates an output dataset with one observation in each by-group, or with one observation only if {cmd:by()} is not specified, and data on estimates, {it:P}-values, {it:z-} or {it:t}-statistics and confidence limits for the weighted sums of parameters within the by-group, or in the whole input dataset if {cmd:by()} is not specified. The weightings for the weighted sums are specified using the {help weight:weight specification}. {p 4 8 2} {cmd:sumvar(}{varlist}{cmd:)} specifies a list of variables in the input dataset to be included in the output dataset, with values equal to their unweighted sums in the input dataset (if {cmd:by()} is not specified) or to their unweighted sums within the by-group (if {cmd:by()} is specified). For instance, if the input dataset contains one observation per study to be entered into a meta-analysis, and contains a variable {hi:N} specifying the number of subjects in the study, then the user can specify {cmd:sumvar(N)}, and {hi:N} will be present in the output dataset, where it will contain the total number of subjects in all the studies. {p 4 8 2} {cmd:dfcombine(}{it:combination_rule}{cmd:)} specifies a rule for combining the degrees of freedom of the input parameters to define the degrees of freedom for the output parameters, if the {it:t}-distribution is used to define confidence limits and {it:P}-values. If {cmd:dfcombine(satterthwaite)} is specified, then the formula of Satterthwaite (1946) is used. If {cmd:dfcombine(welch)} is specified, then the formula of Welch (1947) is used. If {cmd:dfcombine(constant)} is specified, then {helpb metaparm} checks that the degrees of freedom are constant (or constant within by-groups if {cmd:by(}{it:{help varlist}}{cmd:)} is specified), and then sets the output degrees of freedom to the constant input degrees of freedom. {cmd:dfcombine()} is set to {cmd:satterthwaite} by default, but is ignored if the {it:t}-distribution is not used to define confidence limits and {it:P}-values. The option {cmd:dfcombine(constant)} is useful if the input parameters are uncorrelated parameters belonging to the same model estimation with pooled degrees of freedom, such as group means estimated using the {helpb regress} command with group membership indicators as {it:X}-variables, using the {cmd:noconst} option, and the user uses {helpb metaparm} to estimate contrasts of interest, such as differences or interactions. In these circumstances, using {helpb regress} without the {cmd:robust} option and using {cmd:dfcombine(constant)} with {helpb metaparm} gives confidence limits and {it:P}-values equivalent to those of the equal-variance {help ttest:{it:t}-test}. By contrast, if the user estimates group means using a separate constant-only model for each group, and then uses {helpb metaparm} with the option {cmd:dfcombine(satterthwaite)} or {cmd:dfcombine(welch)}, then the confidence limits and {it:P}-values are equivalent to those of the Satterthwaite or Welch unequal-variance {help ttest:{it:t}-test}. {p 4 8 2} {cmd:idnum(}{it:#}{cmd:)} specifies an ID number for the output dataset. It is used to create a numeric variable, with default name {hi:idnum}, in the output dataset, with that value for all observations. This is useful if the output resultsset is concatenated with other resultssets using {helpb append}. {p 4 8 2} {cmd:nidnum(}{help newvar:{it:newvarname}}{cmd:)} specifies a name for the numeric ID variable evaluated by {cmd:idnum()}. If {cmd:idnum()} is present and {cmd:nidnum()} is absent, then the name of the numeric ID variable is set to {hi:idnum}. {p 4 8 2} {cmd:idstr(}{it:string}{cmd:)} specifies an ID string for the output dataset. It is used to create a string variable, with default name {hi:idstr}, in the output dataset, with that value for all observations. This is useful if the output resultsset is concatenated with other resultssets using {helpb append}. {p 4 8 2} {cmd:nidstr(}{help newvar:{it:newvarname}}{cmd:)} specifies a name for the string ID variable evaluated by {cmd:idstr()}. If {cmd:idstr()} is present and {cmd:nidstr()} is absent, then the name of the string ID variable is set to {hi:idstr}. {p 4 8 2} {cmd:format(}{it:{help varlist:varlist_1} {help format:format_1} ... {help varlist:varlist_n} {help format:format_n}}{cmd:)} specifies a list of pairs of {help varlist:variable lists} and {help format:display formats}. The {help format:formats} will be allocated to the variables in the output dataset specified by the corresponding {help varlist:{it:varlist}s}. {title:Author} {pstd} Roger Newson, King's College London, UK. Email: {browse "mailto:roger.newson@kcl.ac.uk":roger.newson@kcl.ac.uk} {title:References} {phang} Satterthwaite, F. E. 1946. An approximate distribution of estimates of variance components. {it:Biometrics Bulletin} 2(6): 110-114. {phang} Welch, B. L. 1947. The generalization of `Student's' problem when several different population variances are involved. {it:Biometrika} 34(1/2): 28-35. {title:Also see} {psee} Manual: {manlink D append}, {manlink D format} {p_end} {psee} {space 2}Help: {manhelp append D}, {manhelp format D}{break} {helpb parmest}, {helpb parmby}, {helpb parmcip}, {helpb metaparm}, {help metaparm_outdest_opts:{it:metaparm_outdest_opts}}, {help parmcip_opts:{it:parmcip_opts}}, {help metaparm_resultssets:{it:metaparm_resultssets}} {p_end}