Package: restriktor 0.6-50

Goal GORIC(A) | GORIC(A) output | GORIC(A) values | GORIC(A) weights and ratios | Hypotheses sets | Interpretation output | General | One informative hypothesis | vs Complement | Example | vs Unconstrained | Multiple informative hypotheses | Complement as failsafe | Unconstrained as failsafe | No failsafe | Note: Hypothesis specification | Special cases | Equal fit | Overlapping hypotheses | Example: Subset true | Example: Non-overlapping part true | Follow-up exploratory analysis for non-overlapping part | Support for boundary | Example: $H_1$ versus its complement | Follow-up exploratory analysis for boundary | Example: $H_1$, $H_2$, and the unconstrained | Notes | Just below maxmimum fit | Equality restriction (=) | About-equality restrictions | Not highest fit | Example: Correct hypothesis | Example: Incorrect hypothesis | Note on sample size | Remarks Bayesian model selection | Example: Prior sensitivity bain | Example: Support for incorrect equality | N = 100 | N = 1000 | bain | GORIC | N = 10000

Introduction | GORIC(A) weights benchmarks | How to use benchmarks | Labelling | Use minimum effect | Sensitivity analysis | Defaults | General R code | Examples | Example 1 (ANOVA): $H_1$ vs its complement | Footnote | Example 2 (ANOVA): Overlapping hypotheses | Log-likelihood benchmarks | Example 3 (ANOVA): Border is true | Higher sample size | Example 1 (ANOVA) Ctd.

Packages | Example 1: Confirmatory Factor Analysis | Example 2: Multiple Group CFA | Measurement invariance | Hypothesis evaluation using GORICA | Example 3: Structural equation modeling (SEM) | Example 4: Multilevel SEM | Example 5: linear growth model with a time-varying covariate | Example 6: Mediation

Examples with R code | Example 1: Relationship previous experience and trust | Data preparation | Data for evSyn | Hypotheses | GORICA Evidence Synthesis | Example 2: Comparing surgical and non-surgical treatments for periodontal disease | Background Information & Data | Set 1 | Set 2 | Set 3 | Specifying sets of hypotheses in evSyn | Types of input for evSyn | using Estimates and Covariance Matrix | using GORIC(A) Values | using GORIC(A) Weights | Note | using Log-likelihood and Penalty Values