scholarly journals Maximum likelihood, multiple imputation and regression calibration for measurement error adjustment

2008 ◽  
Vol 27 (30) ◽  
pp. 6332-6350 ◽  
Author(s):  
Karen Messer ◽  
Loki Natarajan
Keyword(s):  
Maximum Likelihood ◽  
Measurement Error ◽  
Multiple Imputation ◽  
Regression Calibration ◽  
Error Adjustment

Gencrm: A New Command for Generalized Continuation-Ratio Models

2018 ◽  
Vol 18 (4) ◽  
pp. 924-936 ◽  
Author(s):  
Shawn Bauldry ◽  
Jun Xu ◽  
Andrew S. Fullerton
Keyword(s):  
Maximum Likelihood ◽  
Multiple Imputation ◽  
Common Factors ◽  
Modeling Processes ◽  
Ratio Model ◽  
Complete Coverage ◽  
Link Functions ◽  
Continuation Ratio ◽  
Job Promotion ◽  
Parameter Constraints

A continuation-ratio model represents a variant of an ordered regression model that is suited to modeling processes that unfold in stages, particularly those in which a return to a previous stage is not possible (for example, educational attainment, job promotion, or disease progression). The parameters for covariates in continuation-ratio models may be constrained to be equal, vary by a set of common factors (that is, proportionality constraints), or freely vary across stages. Currently, there are three community-contributed commands that fit continuation-ratio models. Each of these commands fits some subset of continuation-ratio models involving parameter constraints, but none of them offer complete coverage of the range of possibilities. The new gencrm command expands the options for continuation-ratio models to include the possibility for some of or all the covariates to be constrained to be equal, to freely vary, or to vary by a set of common factors across stages. gencrm relies on Stata's maximum likelihood routines for estimation and avoids reshaping the data. gencrm includes options for three link functions (logit, probit, and cloglog) and supports Stata's multiple-imputation suites of commands.

scholarly journals The efficiency of multiple imputation and maximum likelihood methods for estimating missing values

2018 ◽  
Vol 11 (16) ◽  
pp. 1-11
Author(s):  
Tlhalitshi Volition Montshiwa ◽  
Ntebo Moroke ◽  
Elias Munapo ◽  
◽  
◽  
...  
Keyword(s):  
Maximum Likelihood ◽  
Multiple Imputation ◽  
Missing Values ◽  
Likelihood Methods ◽  
Maximum Likelihood Methods
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