The process was developed for an individual patient data meta-analysis (IPD-MA) because the author's team was faced with the problem of creating a standard, uniform model that would push all available covariates through SAS/STAT(R) software's PROC LOGISTIC allowing results to be compared among...
Multiple lesions from the same individual were treated as independent because the effect on the participant was not significant (logistic regression model). Details are provided in the eMethods in the Supplement. Statistical analyses used Prism, version 7.0 (GraphPad), and SAS, version 9.3 (SAS ...
John H. McDonald
Software code for all three methods in SAS is provided. Copyright 2008 John Wiley & Sons, Ltd. 展开 关键词: measurement error maximum likelihood multiple imputation regression calibration DOI: 10.1002/sim.3458 被引量: 43 年份: 2010 收藏 引用 批量引用 报错 分享 ...
Again, ODS TRACE is used to find the names of the objects used by PROC LOGISTIC. Figure 5 is an extract of the SAS LOG showing the 10 objects generated by PROC LOGISTIC. ODS TRACE ON; PROC LOGISTIC DATA=mydata DESCENDING; CLASS DaysMix (PARAM=REF REF="None"); MODEL asthma = Days...
Data were analysed using the logistic procedure ofSAS. Coefficients for stalk number, height, diameter and number of eldana bored stalks were highly significant(p < 0.0001), which indicated their influence in selecting for high cane yield. Selected genotypes in BSL13 produced20% more stalks that...
2019: %svy_logistic_regression: A generic SAS macro for simple and multiple logistic regression and creating quality publication-ready tables using survey or non-survey data Plos one 14(9): E0214262Harder, T.; Pappi, F.U. 1969: Multiple-level regression analysis of survey and ecological data...
Analyses were conducted using SAS software, version 9.1 (SAS Institute Inc, Cary, NC). Results The main characteristics of the cases and controls are shown in the Table. Multiple sclerosis cases were, on average, 28.5 years old (age range, 18-48 years) at symptom onset. The initial disease...
Age at onset, education, smoking, and alcohol status were considered as confounding factors (i.e. additional covariates) in the multivariable logistic models. A two-sided p-value <0.05 was considered for statistical significance. All statistical analyses were performed using SAS Release 9.4 (SAS ...
Baseline adjusted survival time was analyzed using the Cox proportional hazard model and baseline adjusted categorical data were analyzed using logistic regression. In the analysis of new T1-weighted hypointensive lesions, the missing MRI assessments were set to zero as a conservative approach, since ...