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【正文】 SAS documentation on PROC MIANALYZE 49 Software 3. SOLAS version ($1K) Windows based software that performs different types of imputation: ? Hotdeck imputation ? Predictive OLS/discriminant regression ? Nonparametric based on propensity scores ? Last value carried forward Will also bine parameter results across the M analyses. 50 MI Analysis of the Orthodontic Growth Data 51 Properties of methods ? MCAR: dropout independent of response ? CC is valid, though it ignores information ? LOCF is valid if there are no trends with time ? MAR: dropout depends only on observations ? CC, LOCF, GEE invalid ? MI, MNLM, weighted GEE valid ? MNAR: dropout depends also on unobserved ? CC, LOCF, GEE, MI, MNLM invalid ? SM, PMM valid if (uncheckable) assumptions true 52 References ? Allison, P. (2022). Missing data. Thousand Oaks, CA: Sage [greenback]. ? Horton, NJ amp。 Lipsitz, SR. (2022) Multiple imputation in practice: Comparison of software packages for regression models with missing variables. The American Statistician 55(3): 244254. ? Little, . (1992) Regression with missing X’s: A review. Journal of the American Statistical Association 87(420):12271237. ? Roderick J. A. Little and Donald B. Rubin (2022) Statistical Analysis with Missing Data, 2nd edition April 2022, Applications of Modern Missing Data Methods, by Roderick J. A. Little. ? by Joseph L. Schafer Joe Schafer’s (1997) Analysis of Inplete Multivariate Data, web site: ? Anderson, . (1956) Maximum likelihood estimates for a multivariate normal distribution when some observations are missing. 53 Further References ? Little, RL amp。 Rubin, DB. (1st ed. 1990, 2nd ed. 2022). Statistical analysis with missing data. New York: Wiley. ? Rubin, DB. (1987). Multiple imputation for survey nonresponse. New York: Wiley. ? Mallinckrodt et al. (2022). Assessing and interpreting treatment effects in longitudinal clinical trials with missing data. Biological Psychiatry 53, 754–760. ? Gueuieva amp。 Krystal (2022) Move Over ANOVA. Archives of General Psychiatry 61, 310–317. ? Mallinckrodt et al. (2022). Choice of the primary analysis in longitudinal clinical trials. Pharmaceutical Statistics 3, 161–169. ? Molenberghs et al. (2022). Analyzing inplete longitudinal clinical trial data (with discussion). Biostatistics 5, 445–464. ? Cook, Zeng amp。 Yi (2022). Marginal analysis of inplete longitudinal binary data: a cautionary note on LOCF imputation. Biometrics 60, 820828. 54 Date Name, department 55 Any Questions?
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