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The model estimation procedure is executed via GAUSS 8.0 [36].Thexplanatoryry variables tested for the cross-sectional binary logit model include age, age square, gender, years of driving experience, driver type, expressway use frequency, travel time saving, cause of expressway delay, and number of traffic lights on the arterial road.
The covariates included in the model include AGE, 70G, CSR, and CERBB.
Input parameters in the COPD disease model include age, gender distribution, body mass index, cardiovascular and other comorbidities, prior exacerbation history, smoking status and health status measured by the SGRQ or St George's Respiratory Questionnaire for COPD (SGRQ-C).
The risk factors in this model include age, age at menarche, age at first live birth, number of previous biopsies, presence of atypical hyperplasia on biopsy, and number of first-degree relatives with breast cancer.
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A model including age, FR, vocabulary, and spatial skills accounted for 90% of the variance in future math achievement.
The initial model included age and baseline PaO2/FiO2.
Model includes age controls (indicators for 4 age brackets), urban dummy.
The control variables in the model included age, education, family income, and number of chronic diseases.
The model included age, gender, level of education, marital status and use of HURT.
The parsimonious model includes age at the time of the biopsy, industry that the incident occurred, and cancer type.
Results indicated that variables suggested by the Andersen model, including age, depression, psychological aggression, and posttraumatic stress-related arousal symptoms, were significant predictors of help-seeking.
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CEO of Professional Science Editing for Scientists @ prosciediting.com