Package TestDataImputation
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1 Type Package Package TestDataImputation August 11, 2016 Title Missing Item Responses Imputation for Test and Assessment Data Version 1.0 Date Author Shenghai Dai [aut, cre], Xiaolin Wang [aut], Dubravka Svetina [aut] Maintainer Shenghai Dai Functions for imputing missing item responses for dichotomous and polytomous test and assessment data. This package enables missing imputation methods that are suitable for test and assessment data, including: listwise (LW) deletion, treating as incorrect (IN), person mean imputation (PM), item mean imputation (IM), two-way imputation (TW), logistic regression imputation (LR), and EM imputation. Depends R (>= 3.2.5), mice, Amelia, stats NeedsCompilation no LazyData true License GPL (>= 2) RoxygenNote Repository CRAN Date/Publication :40:22 R topics documented: EMimpute ImputeTestData ItemMean Listwise LogsticReg PersonMean TreatIncorrect Twoway
2 2 ImputeTestData Index 9 EMimpute EM Imputation This function imputes for all missing responses using EM imputation. Integrated scores are obtained by rounding imputed values to the closest possible response value. EMimpute(, = "NA", = 1) values are coded as NA or other values (e.g., 8, 9). Missing response indicators in the data (e.g. "NA", "8", "9", etc.). ="NA" A data frame with all missing responses replaced by integrated imputed values. EMimpute(, ="8",=1) ImputeTestData This main function imputes for missing responses using selected method This function imputes for all missing responses using selected miputation methods. Integrated scores are obtained by rounding imputed values to the closest possible response value. ImputeTestData(, = "NA", = 1, method = "LW")
3 ItemMean 3 method values are coded as NA or other values (e.g., 8, Missing response indicators in the data (e.g. "NA", "8", "9", etc.). ="NA" by Missing response indicators in the data (e.g. "NA", "8", "9", etc.). ="NA" Missing response imputation methods. "LW" (by default) represents listwise that deletes all examinees who reported missing responses; "IN" means treating all missing responses as incorrect; "PM" imputes for all missing responses of an examinee by his/her mean on the available items; "IM" imputes for all missing responses of an item by its mean on the available responses; "TW" imputes for all missing responses using two-way imputation.; "LR" imputes for all missing responses using logistic regression; "EM" imputes for all missing responses using EM imputation. A data frame with all missing responses replaced by integrated imputed values. ImputeTestData(, ="8",=1, method ="TW") ItemMean Item Mean (IM) Imputation This function imputes for all missing responses of an item by its mean (i.e., IM) on the available responses. Integrated scores for items are obtained by rounding their means to the closest possible response value. ItemMean(, = "NA", = 1) values are coded as NA or other values (e.g., 8, 9). Missing response indicators in the data (e.g. "NA", "8", "9", etc.). ="NA"
4 4 Listwise A data frame with all missing responses replaced by Integrated item means. ItemMean(, ="8",=1) Listwise Listwise Deletion (LW) This function deletes examinees who report missing responses. Listwise(, = "NA") values are coded as NA or other values (e.g., 8, Missing response indicators in the data (e.g. "NA", "8", "9", etc.). ="NA" by Missing response indicators in the data (e.g. "NA", "8", "9", etc.). ="NA" A data frame with no missing responses. Listwise(, ="8")
5 LogsticReg 5 LogsticReg Logistic Regression (LR) Imputation This function imputes for all missing responses using logistic regression. Integrated scores are obtained by rounding imputed values to the closest possible response value. LogsticReg(, = "NA", = 1) values are coded as NA or other values (e.g., 8, 9). Missing response indicators in the data (e.g. "NA", "8", "9", etc.). ="NA" A data frame with all missing responses replaced by integrated imputed values. LogsticReg(, ="8",=1) PersonMean Person Mean Imputation (PM) This function imputes for all missing responses of an examinee by his/her mean (i.e., PM) on the available items. Integrated scores for examinees are obtained by rounding their means to the closest possible response value. PersonMean(, = "NA", = 1)
6 6 values are coded as NA or other values (e.g., 8, Missing response indicators in the data (e.g. "NA", "8", "9", etc.). ="NA" by Missing response indicators in the data (e.g. "NA", "8", "9", etc.). ="NA" A data frame with all missing responses replaced by person means. References Sijtsma, K., & Van der Ark, L. A. (2003). "Investigation and treatment of missing item scores in test and questionnaire data." Multivariate Behavioral Research, 38(4), PersonMean(, ="8",=1) Example test data Format This dataset contains binary responses of 775 participants to 20 items.missing responses are coded as NA. data("") A data frame with 775 observations on the following 20 items. Item_1 a numeric vector Item_2 a numeric vector Item_3 a numeric vector Item_4 a numeric vector Item_5 a numeric vector Item_6 a numeric vector
7 TreatIncorrect 7 Details Item_7 a numeric vector Item_8 a numeric vector Item_9 a numeric vector Item_10 a numeric vector Item_11 a numeric vector Item_12 a numeric vector Item_13 a numeric vector Item_14 a numeric vector Item_15 a numeric vector Item_16 a numeric vector Item_17 a numeric vector Item_18 a numeric vector Item_19 a numeric vector Item_20 a numeric vector A test data that contain binary responses of 775 participants to 20 items.missing responses are coded as NA. data() ## maybe str() ; plot()... TreatIncorrect Treat missing responses as incorrect (IN) This function replaces all missing responses by zero. TreatIncorrect(, = "NA") values are coded as NA or other values (e.g., 8, Missing response indicators in the data (e.g. "NA", "8", "9", etc.). ="NA" by Missing response indicators in the data (e.g. "NA", "8", "9", etc.). ="NA"
8 8 Twoway A data frame with all missing responses imputed. TreatIncorrect(, ="8") Twoway Two-Way Imputation (TW) This function imputes for all missing responses using two-way imputation. Integrated responses are obtained by rounding imputed values to the closest possible response value. Twoway(, = "NA", = 1) values are coded as NA or other values (e.g., 8, Missing response indicators in the data (e.g. "NA", "8", "9", etc.). ="NA" by Missing response indicators in the data (e.g. "NA", "8", "9", etc.). ="NA" A data frame with all missing responses replaced by integrated two-way imputed values. References Bernaards, C. A., & Sijtsma, K. (2000). " Influence of imputation and EM methods on factor analysis when item nonresponse in questionnaire data is nonignorable." Multivariate Behavioral Research, 35(3), Twoway(, ="8",=1)
9 Index Topic datasets, 6 EMimpute, 2 ImputeTestData, 2 ItemMean, 3 Listwise, 4 LogsticReg, 5 PersonMean, 5, 6 TreatIncorrect, 7 Twoway, 8 9
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