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help for imputeitems                                       Jean-Benoit Hardouin
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Imputation of missing item responses

        imputeitems varlist [if] [,prefix(string) method(string) random
              max(#)]


Description

    imputeitems imputes missing item responses by different ways : Item Mean
    Substitution (IMS), Person Mean Substitution (PMS), Corrected Item Mean
    Substiutution (CIM), Interitem Correlation Substitution (ICS), logistic
    model (LOG) and Worst Case (WORST). A random process can be added to
    several methods.

Options

    prefix defines the prefix to use to name the imputted variables (this
        prefix is followed by the name of the initial variable). By default,
        this prefix is "imp".

    method defines the method to impute missing data :

        pms computes the proportion of positive response of each individual
        on non missing items, and impute a deterministic result (if p<.5 then
        0, else 1),

        ims computes the proportion of positive response to each items, and
        impute a deterministic result (if p<.5 then 0, else 1),

        cim computes the proportion of positive response to each items,
        corrected by the ability of the individual and impute a deterministic
        result (if p<.5 then 0, else 1),

        ics searchs for each item the more correlated item and replaces a
        missing data by the data of this more correlated item (if the other
        response is missing too, there is no imputation),

        log explains the responses of each item by a logistic model where the
        independent variables are the responses to the others items. Only
        significant variables are rettained (5%). These methods impute a
        deterministic result (if p<.5 then 0, else 1) [log] to missing
        responses (if the response to an independant variable is missing,
        there is no imputation),

        worst replaces the missing data by a 0.

    random adds a random effect to the imputation process (available only
        with pms, ims, cim or log). In these cases, the imputed value is
        randomly drawed from a binomial distribution using the parameter p.

    max allows imputing missing values only for individuals with a maximal
        number of missing values defined with this option.

    By default, pms method is working.

    Old names of methods (bip, {bii}, bic and bil continues to run. They
        actually correspond to the add of the random option to the pms, ims,
        cim and log methods.


Example

        . imputeitems itemA* /*PMS method, IMP prefix*/

        . imputeitems itemA*, prefix(cim) method(cim)

        . imputeitems itemA*, method(log) random


Reference

    Huisman M. (2000), Imputation of missing item responses: some simple
        techniques.  Quality & Quantity, 34, 331-351.


Author

    Jean-Benoit Hardouin, PhD, assistant professor
    EA 4275 "Biostatistics, Clinical Research and Subjective Measures in
        Health Sciences"
    University of Nantes - Faculty of Pharmaceutical Sciences
    1, rue Gaston Veil - BP 53508
    44035 Nantes Cedex 1 - FRANCE
    Email:  jean-benoit.hardouin@univ-nantes.fr
    Websites AnaQol and FreeIRT