ResearchTopics Publications In progress publications Communications
PackagesAnaQol Project PRO-online R Packages Online R-package
Life of the unitProjects Collaborations PhD thesis Traineeships Traineeships propositions Seminars
25 juillet 2019
28 juin 2019
01 juin 2019
01 mai 2019
11 avril 2019
Updated19 août 2019
The Stata module "Imputeitems"
imputeitems imputes missing item responses by different ways : Item Mean Substitution (IMS and BII), Person Mean Substitution (PMS and BIP), Corrected Item Mean Substiutution (CIM and BIC), Interitem Correlation Substitution (ICS), logistic model (LOG and BIL) and worst case (WORST).
Type "findit imputeitems" or "ssc install imputeitems" directly from your Stata browser.
Syntax (version 2.4)
imputeitems varlist [, prefix(string) method(keyword) random max(#) noround ]
- prefix(string): 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(keyword): defines the method to impute missing data:
- pms and bip compute the proportion of positive response of each individual on non missing items, and impute a deterministic result (if p<.5 then 0, else 1) [pms] or a random draw [bip] to missing responses,
- ims and bii compute the proportion of positive response to each items, and impute a deterministic result (if p<.5 then 0, else 1) [ims] or a random draw [bii] to missing responses,
- cim and bic compute 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) [cim] or a random draw [bic] to missing responses,
- 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 and bil explain 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] or a random draw [bil] 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: 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.
- Avoids to round the imputed values to the nearest integer
imputeitems itemA*, prefix(cim) method(cim)
imputeitems itemA*, method(log)