ABSTRACT
Multilevel Models are widely used in organizational research, educational research, epidemiology, psychology, biology and medical fields. In this paper, we recommend the situations where Bootstrap procedures through Minimum Norm Quadratic Unbiased Estimator (MINQUE) can be extremely handy than that of Restricted Maximum Likelihood (REML) in multilevel level linear regression models. In our simulation study the bootstrap by means of MINQUE is superior to REML in conditions where normality does not hold. Moreover, the real data application also supports our findings in terms of accuracy of estimates and their standard errors.
Subject(s)
Models, Statistical , Humans , Likelihood Functions , Multilevel Analysis , Regression AnalysisABSTRACT
Educational researchers, psychologists, social, epidemiological and medical scientists are often dealing with multilevel data. Sometimes, the response variable in multilevel data is categorical in nature and needs to be analyzed through Multilevel Logistic Regression Models. The main theme of this paper is to provide guidelines for the analysts to select an appropriate sample size while fitting multilevel logistic regression models for different threshold parameters and different estimation methods. Simulation studies have been performed to obtain optimum sample size for Penalized Quasi-likelihood (PQL) and Maximum Likelihood (ML) Methods of estimation. Our results suggest that Maximum Likelihood Method performs better than Penalized Quasi-likelihood Method and requires relatively small sample under chosen conditions. To achieve sufficient accuracy of fixed and random effects under ML method, we established ''50/50" and ''120/50" rule respectively. On the basis our findings, a ''50/60" and ''120/70" rules under PQL method of estimation have also been recommended.
Subject(s)
Multilevel Analysis/methods , Research Design/standards , Computer Simulation , Guidelines as Topic , Humans , Likelihood Functions , Logistic Models , Sample SizeABSTRACT
For most of the time, biomedical researchers have been dealing with ordinal outcome variable in multilevel models where patients are nested in doctors. We can justifiably apply multilevel cumulative logit model, where the outcome variable represents the mild, severe, and extremely severe intensity of diseases like malaria and typhoid in the form of ordered categories. Based on our simulation conditions, Maximum Likelihood (ML) method is better than Penalized Quasilikelihood (PQL) method in three-category ordinal outcome variable. PQL method, however, performs equally well as ML method where five-category ordinal outcome variable is used. Further, to achieve power more than 0.80, at least 50 groups are required for both ML and PQL methods of estimation. It may be pointed out that, for five-category ordinal response variable model, the power of PQL method is slightly higher than the power of ML method.
Subject(s)
Biomedical Research/methods , Research Design , Algorithms , Biomedical Research/standards , Computer Simulation , Data Collection , Data Interpretation, Statistical , Humans , Likelihood Functions , Malaria/therapy , Models, Statistical , Multilevel Analysis/methods , Regression Analysis , Reproducibility of Results , Sample Size , Statistics as Topic , Treatment Outcome , Typhoid Fever/therapyABSTRACT
OBJECTIVE: To investigate the association of cryoglobulinaemia and autoimmune markers with hepatitis C virus (HCV) infection in patients on maintenance haemodialysis (HD) and post renal transplantation. METHODS: Serum samples of 103 HCV-antibody (anti-HCV) positive and 105 anti-HCV negative patients were investigated for cryoglobulins. These comprised 136 patients on HD and 72 renal transplant recipients. Serum creatinine and liver function tests were obtained on all patients. Rheumatoid factor (RF), anti nuclear antibodies (ANA), anti smooth muscle antibodies (ASMA), liver kidney microsomal antibodies (LKM), immunoglobulins (Igs) and complement levels were performed on all cryoglobulin positive (cryopositive) samples. HCV RNA and genotyping detection tests were done for cryopositive patients. RESULTS: The prevalence of cryoglobulins in patients on HD or after renal transplantation was found to be higher (57.6%) among anti-HCV positive patients compared to the anti-HCV negative patients (42.4%) (P=0.000). RF, ANA and ASMA were also higher in cryopositive HCV infected patients. HCV RNA was present in 84.2% of anti-HCV positive patients. Cryoprecipitable RF activity was found in a higher number of symptomatic patients with HCV genotype 1 compared to HCV genotype 3. CONCLUSION: There is an association of cryoglobulinaemia and autoimmune markers in HCV infected patients on HD, and in HCV positive renal transplant recipients. Also HCV genotype 1 is associated with symptomatic mixed cryoglobulinaemia.
