The goal of this study was to determine under what conditions single-level and multilevel estimators outperform one another in the context of a two-stage sampling design with unequal probabilities of selection. Monte Carlo simulation methods were used to evaluate the impact of several factors, ...
(sample) coefficient vector constraints matrix iteration log gradient vector variance–covariance matrix of the estimators model-based variance marks estimation sample In addition to the above, the following is stored in r(): Matrices r(table) matrix containing the coefficients with their standard ...
estimators xtnbreg — Fixed-effects, random-effects, & population-averaged negative binomial models 11 Functions e(sample) marks estimation sample In addition to the above, the following is stored in r(): Matrices r(table) matrix containing the coefficients with their standard errors, test ...
Results indicated that the unweighted estimators performed similarly across conditions, whereas the weighted single-level estimators tended to outperform the weighted multilevel estimators, particularly under non-ideal sample conditions. Multilevel weight approximation methods did not perform well when the ...
() specification for margins factor variables fvset as asbalanced factor variables fvset as asobserved coefficient vector constraints matrix iteration log gradient vector variance–covariance matrix of the estimators model-based variance marks estimation sample In addition to the above, the following is ...
(sample) coefficient vector constraints matrix iteration log gradient vector variance–covariance matrix of the estimators model-based variance marks estimation sample In addition to the above, the following is stored in r(): Matrices r(table) matrix containing the coefficients with their standard ...