All of our principals have PhDs at leading universities, including Harvard, Stanford, and Columbia. They include nationally renowned scholars. They have extensive backgrounds in biostatistics and over 100 years of practical experience in quantitative and qualitative methods. They are experts in statistical analysis (e.g., linear regression, logistic regression, hierarchical regression analysis, correlation analysis, chi-square test, t-test, ANOVA, MANOVA, structural equation modeling (SEM), multilevel SEM, confirmatory factor analysis (CFA), Multilevel CFA, factor analysis, principal components analysis, time series analysis, Cox regression, Kaplan-Meier survival analysis, hierarchical linear modeling (HLM), meta-analysis, predictive modeling, cluster analysis, Bayesian analysis, latent class analysis, longitudinal growth modeling, mixture model, linear mixed models, distribution analysis, ensemble analysis, de-identification, trend analysis, sensitivity analysis, negative binomial regression, interim analysis, decision tree, item analysis, nonparametric test, and advanced statistical analysis). They are experts in statistical programming languages such as SPSS, SAS, Stata, R, HLM, Mplus, SPSS Amos, SPSS Modeler, Azure, JMP, WinBUGS, Minitab, Match!3, and Access. They are experts in using qualitative data analysis software such as NVivo, Nud*ist, HyperResearch, and Atlas.