Looking for help with a specific technique?  Here's an expanded list from our toolkit.

Surveys and psychometrics

• Survey and questionnaire design
• Scale development:  distilling multiple items into themes and quantifying each person's score
• Testing for survey bias, including straightlining; preferences for consistent or extreme or middle responses; social desirability bias; or common method bias
• Validation
• Multitrait, multimethod analysis
• Reliability analysis, including Cronbach’s alpha and Cohen’s kappa
• Exploratory factor analysis (EFA) and principal component analysis (PCA)
• Multidimensional scaling
• Cluster analysis
• Pricing analysis, including Van Westendorp, Gabor-Granger, monadic, vignette, conjoint, market basket, and behavioral-economics techniques

 
Univariate and bivariate statistical methods

• Z-tests and T-tests of mean differences
• Correlation; manipulation of correlation coefficients using Fisher’s Z; adjustments for attenuation
• Non-parametric measures of association (e.g., phi, Cramer’s V, Somers’ D, Hoeffding’s D)
• Effect sizes (e.g., Cohen’s d, R-squared, eta-squared, f, pseudo-R-squared alternatives, concordance, odds ratios, risk ratios)
• Chi-square testing
• Analysis of proportions and the differences between them
• Analysis of distributions (e.g., normal, bimodal, poisson, lognormal)

 
Types of regression and related predictive or explanatory multivariate models

• Predictive modeling, predictive analytics, risk scoring, machine learning
• Multiple linear regression
• Analysis of variance (ANOVA)
• Analysis of covariance (ANCOVA) and analysis of gain scores (change scores)
• Multiple logistic regression (including binary and multinomial)
• Least Absolute Shrinkage and Selection Operator (LASSO) regression
• Survival analysis and regression incorporating censoring
• Instrumental variables and Two-Stage Least Squares (2SLS) analysis
• Time series analysis, including autocorrelation and Autoregressive Integrated Moving Average (ARIMA) models
• Random forest models

 
Approaches that can enhance modeling

• Power analysis
• Variable selection techniques, both automated and intentional, including sequential and stepwise modeling
• Data transformations
• Modeling of nonlinear effects
• Modeling of interaction effects, including Chi-Square-Based Automatic Interaction Detection (CHAID)
• Model diagnostics, including analysis of outliers, leverage, residuals, linearity, and multicollinearity
• Partial and semipartial correlations
• Imputation of missing data (including Multiple Imputation using Chained Equations, or MICE)
• Receiver Operating Characteristic (ROC) curves and Area Under the Curve (AUC)
• Cross-validation (e.g., k-fold)
• Sensitivity analysis
• Monte Carlo simulation
• A wide variety of methods for creating data graphics -- for exploring data, illuminating findings, and instructing or persuading an audience

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