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64 lines
3.2 KiB
Plaintext
64 lines
3.2 KiB
Plaintext
9 months ago
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{* 30june2008}{...}
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{hline}
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help for {hi:imputerasch}{right:Jean-Benoit Hardouin}
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{hline}
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{title:Imputation of missing binary variables by a Rasch model}
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{p 8 14 2}{cmd:imputerasch} {it:varlist} [{cmd:,} {cmdab:pref:ix}({it:string}) {cmdab:noran:dom} {cmdab:savep:roba}({it:string}) {cmdab:nbit:eration}({it:#}) {cmdab:det:ails} {cmdab:max}({it:#})]
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{p 8 14 2}{it:varlist} is a list of two or more existing dichotomous variables.
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{title:Description}
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{p 4 8 2}{cmd:imputerasch} imputes missing binary data by a Rasch model.
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The parameters of the Rasch model are estimated on complete data, then the missing data are imputed from the estimated probability
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for each individual to response to each item.
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By default, the imputed value is a result of a random draw within a Bernouilli random variable with this probability used like
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parameter, but it is possible to affect more deterministically the value of the missing data (0 if p<0.5 and 1 if p>=.5) with
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the {cmd:norandom} option.
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An iterative procedure can be run in a second time by estimating parameters of the Rasch model on existing and imputing data,
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and by eventually correcting missing data at each step (see the {cmd:nbiteration} option).
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This procedure is stopped as soon the allowed maximal number of iterations is attained, or as soon the imputed values are stable.
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{title:Options}
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{p 4 8 2}{cmd:prefix}. The former variables (with missing data) are keeped. New variables are created by imputing new values to missing data.
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The name of these new variables are the names of the former variables preeceded by the prefix defined in this option. By default, this prefix is "imp".
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{p 4 8 2}{cmd:norandom} avoids to randomly draw the value of imputation (by default). A deterministic process is used : if the expected probability is <0.5, imputed value is 0, else imputed value is 1
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(the old name of this option, {cmd:nobinomial}, continues to run).
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{p 4 8 2}{cmd:saveproba} allows saving the expected probability in variables whose the names begin by the string defined in this option.
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{p 4 8 2}{cmd:nbiteration} realizes an iterative procedure which is stopped as soon as the maximal number of iterations is attained, or as soon as the imputed data are stable.
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{p 4 8 2}{cmd:details} gives details on the imputation.
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{p 4 8 2}{cmd:max} allows imputing missing values only for individuals with a maximal number of missing values defined with this option.
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{title:Example}
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{inp:. imputerasch item*}
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{inp:. imputerasch item*, norandom saveproba(p) prefix(dataimputed) max(4)}
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{inp:. imputerasch item1-item5, nbiteration(5) details}
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{title:Author}
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{p 4 8 2}Jean-Benoit Hardouin, PhD, assistant professor{p_end}
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{p 4 8 2}EA 4275 "Biostatistics, Clinical Research and Subjective Measures in Health Sciences"{p_end}
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{p 4 8 2}University of Nantes - Faculty of Pharmaceutical Sciences{p_end}
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{p 4 8 2}1, rue Gaston Veil - BP 53508{p_end}
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{p 4 8 2}44035 Nantes Cedex 1 - FRANCE{p_end}
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{p 4 8 2}Email:
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{browse "mailto:jean-benoit.hardouin@univ-nantes.fr":jean-benoit.hardouin@univ-nantes.fr}{p_end}
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{p 4 8 2}Websites {browse "http://www.anaqol.org":AnaQol}
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and {browse "http://www.freeirt.org":FreeIRT}
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