Third Millennium Research, Inc. can provide prompt and accurate analysis and can assist with clear and meaningful interpretation of the results.  We take a methodical approach to analysis, have diverse programming capabilities, and are experienced applying a wide variety of statistical and data mining techniques.  No projects are too big or small.  It is important to us that you fully understand why specific techniques are applied, and that the results are informative and enable you to strategically plan or make adjustments to improve your organization’s effectiveness, productivity, and/or efficiency. We strive to apply the most appropriate techniques that render results that readily enable effective, evidence-based decision-making. 

Statistical Techniques. We can apply a wide variety of statistical techniques, ranging from non-parametric tests to multivariate techniques.  These techniques include the general linear model (analysis of variance, ordinary least squares & multiple regression), models with non-normally distributed outcomes (logistic regression, ordinal & multinomial logit modeling, Poisson, negative binomial, Cox, and probit regression), causal modeling techniques (e.g., partial, path, & canonical correlation analysis, and structural equations modeling), and techniques designed to establish dimensionality (exploratory & confirmatory factor analysis, latent trait analysis, item response theory).  Other techniques include multilevel or hierarchical linear modeling, event history analysis, hazards modeling, longitudinal data analysis (e.g., generalized estimating equations & mixed/random effects modeling), survival analysis, life table analysis, and missing data analysis (e.g.,  multiple imputation), and statistical power analysis.

Data Mining Techniques.   Depending on your research questions, we can apply a variety of either descriptive or predictive data mining techniques.  With exploratory techniques (e.g., factor analysis via principle components, correspondence, or multiple correspondence algorithms) our objective is to reduce, summarize and group data, and there is no dependent or outcome variable.   With predictive techniques, our objective is to explain data with regard to a dependent or outcome variable.   There are a wide variety of predictive techniques and associated algorithms that we can employ, including decision trees (e.g, classification & regression trees), neural networks, parametric & semi-parametric models, and probabilistic analysis (e.g, k-nearest neighbors).  The specific algorithms we employ are contingent upon the type and level of measurement of your dependent variable(s).

Data Security and Confidentiality.  Data security, confidentiality, and the privacy of research participants and your data are very high priorities for us.  We maintain very rigorous data security protocols, only use encrypted data storage, require secure data transfers, and strictly adhere to human subjects protocols.  We also respect that some clients wish to maintain a strictly confidential and private relationship with our firm. Thus, without our clients’ written, expressed consent, we will not disclose their identity, their research projects, or findings with anyone outside of our firm.