Introduction | Operating System and Installation | Data Setup | Example Data | Creating a Genotype Matrix | Preview Missing Data: summaryGeno | Haplotype Frequency Estimation: haplo.em | Algorithm | Example Usage haplo.em() | Summary Method | Control Parameters for haplo.em | Setting Seed for Reproducable haplotype estimation | Haplotype Frequencies by Group Subsets | Power and Sample Size for Haplotype Association Studies | Quantitative Traits: haplo.power.qt | Case-Control Studies: haplo.power.cc | Haplotype Score Tests: haplo.score | Quantitative Trait Analysis | Binary Trait Analysis | Ordinal Trait Analysis | Warning for Ordinal Traits | Haplotype Scores, Adjusted for Covariates | Plots and Haplotype Labels | Skipping Rare Haplotypes\label | Score Statistic Dependencies: the eps.svd parameter | Haplotype Model Effect | Simulation p-values | Regression Models: haplo.glm | New and Updated Methods for haplo.glm | Preparing the data.frame for haplo.glm | Rare Haplotypes | Regression for a Quantitative Trait | Fitting Haplotype x Covariate Interactions | Regression for a Binomial Trait | Caution on Rare Haplotypes with Binomial Response | Control Parameters | Controlling Genetic Models: haplo.effect | Selecting the Baseline Haplotype \label | Rank of Information Matrix and eps.svd | Rare Haplotypes and haplo.min.info | Methods for haplo.glm | fitted.values | residuals | vcov | anova and Model Comparison | Extended Applications | Combine Score and Group Results: haplo.score.merge | Case-Control Haplotype Analysis: haplo.cc | Score Tests on Sub-Haplotypes: haplo.score.slide | Plot Results from haplo.score.slide | Creating Haplotype Effect Columns: haplo.design | Appendix | Counting Haplotype Pairs When Marker Phenotypes Have Missing Alleles

SMART: Dynamic Treatment (DTR) | DTR Calculations | Relative Bias plots | DTR Power comparison-with same initial treatment regimen | DTR Power comparison-with different initial treatment regimens

SMART: Single Sequential Treatment (SST) | SST Calculations | SST Plots | Relative Bias plots, separate for relative mean and relative variance (sigsq) | SST Power

Overview | Simulated dataset | regmed: Mediation model for 1 exposure, multiple mediators, and 1 outcome variable | Pre-filter mediators | Grid of lambda penalties | Fit regmed for grid of lambda penalties | Select best model from grid by minimum BIC | Fit single regmed model with user-specified lambda | Plot directed graph of fit model | Lavaan sem: Estimate parameters of selected model without imposing penalty | mvregmed : Mediation model for multiple exposures, multiple mediators, and multiple outcome variables | Fit mvregmed for a grid for lambda penalties | Select best model from grid based on minimum BIC | Fit single mvregmed model with user-specified lambda | Lavaan sem: Estimate parameters of seleted model without imposing penalty | Interpretation of lavaan output | References

Example Data | Sequential Tests With Covariates

Example Data