Marginally specified generalized linear mixed models: a robust approach.

Longitudinal data modeling is complicated by the necessity to deal appropriately with the correlation between observations made on the same individual. Building on an earlier nonrobust version proposed by Heagerty (1999, Biometrics 55, 688-698), our robust marginally specified generalized linear mixed model (ROBMS-GLMM) provides an effective method for dealing with such data. This model is one of the first to allow both population-averaged and individual-specific inference. As well, it adopts the flexibility and interpretability of generalized linear mixed models for introducing dependence but builds a regression structure for the marginal mean, allowing valid application with time-dependent (exogenous) and time-independent covariates. These new estimators are obtained as solutions of a robustified likelihood equation involving Huber's least favorable distribution and a collection of weights. Huber's least favorable distribution produces estimates that are resistant to certain deviations from the random effects distributional assumptions. Innovative weighting strategies enable the ROBMS-GLMM to perform well when faced with outlying observations both in the response and covariates. We illustrate the methodology with an analysis of a prospective longitudinal study of laryngoscopic endotracheal intubation, a skill that numerous health-care professionals are expected to acquire. The principal goal of our research is to achieve robust inference in longitudinal analyses.

Clinical measurement of the static rear stability of occupied wheelchairs.

OBJECTIVE: To evaluate a new clinical test, platform testing of the static rear stability of wheelchairs occupied by their users (using methods adapted from the International Organization for Standardization [ISO]), from the perspective of its measurement properties, safety, and comfort. DESIGN: Within-subject comparisons. SETTING: Rehabilitation center. PATIENTS: Ninety-seven wheelchair users. MAIN OUTCOME MEASURES: Static stability (with the brakes locked and unlocked, the occupant leaning forward and back, and with antitip devices in place), dynamic stability (the criterion measure), reliability, validity, sensitivity, specificity, predictive values, and likelihood ratios. RESULTS: Test-retest reliabilities (n = 18 to 24) were all >.93. The test's construct validity was demonstrated by the finding that static stability was appropriately affected by locking the brakes, body position, and antitip devices (p < .0001). Spearman's rank correlations between static and dynamic stability ranged from .29 to .65. Sensitivity ranged from 46% to 85%, specificity from 59% to 78%, positive predictive values from 76% to 86%, negative predictive values from 42% to 69%, positive likelihood ratios from 1.56 to 2.95, and negative likelihood ratios from .22 to .71. There were no adverse events, and the subjects tolerated the tests well. CONCLUSIONS: In the clinical setting, the ISO platform test of static rear stability has good to excellent measurement properties, is safe, and is well tolerated. Static-stability testing in this setting should be performed in the context of a comprehensive evaluation of wheelchair safety and performance.