- An agent-based model of coalitions and political instability (see here)
- Inference for a ratio when the denominator could be positive or negative (see here)
- Better than difference in differences (see here)
- Problems with formulations of risk aversion (see here and here)
- Red state blue state now (see here and here)
- Putting race, ethnicity, nationality, religion, and language identities on a common scale
- Poisson or negative binomial regression (see here)
- Interrogating the metaphor of cargo cult science
- Regression discontinuity analysis: What went wrong and how to do better (see here)
- No evidence for a role of maternal adiposity in sex ratio: An example of a hopelessly-noisy statistical analysis in epidemiology
- Model-based winsorizing
- Graphing uncertainty in election forecasting (see here)
- Understanding state-level polling errors
- Effective sample size of the prior distribution (see here)
- Static sensitivity analysis (see here)
- Why it doesnâ€™t make sense in general to form confidence intervals by inverting hypothesis tests (see here)
- When MRP goes bad: Diagnostics and solutions (see here and here)
- A graphical dashboard for MRP
- Experimental design and time variation (see here)
- Instrumental variables with informative priors
- Regularizing using transformations and priors for a meta-analysis of survey incentives (see here)
- Risk aversion as backdoor Bayes
- Meta-analysis for a single study (see here)
- Recalibration of posterior intervals based on approximate computation (see here)
- Meta-analysis combining separate posterior distributions instead of raw estimates
- The gay penumbra: Measurement and time trends (see here)
- You need 16 times the sample size to estimate an interaction than to estimate a main effect (see here and here)
- Implicit assumptions in practically effective methods (see section 7.6 of BDA3)
- Conditional distributions and incoherent Gibbs (see here and here)
- Models for taxonomic structures as an example of the unfolding flower paradigm (see here)
- Domains of efficency for different methods of computing hierarchical linear and logistic regressions
- Effective number of parameters that can be estimated as a function of sample size, with phase transitions for some multilevel models
- Thinking about variation when hypothesizing a plausible average treatment effect (see here)
- A proposed schedule for post-publication review (see here)
- What is a replication?
- Design and sample size analysis for various identification strategies
- Two sides, no vig: The problem with generative and inferential reasoning in social science (see here)
- Using correlation to assess representativeness of a sample
- Displaying uncertainty and variation in hierarchical models
- The Squealer: A sensification of gradients in model fitting
- Phase space of computational algorithms for multilevel regression
- Priors on derived quantities
- Replacing hard constraints with soft constraints
- Advice about writing advice (see here)
- Scaling of group-level variances in hierarchical models (see here)