- Bayesian inference
- Causal inference
- Inference
- Linear regression
- Logistic regression
- Longitudinal and clustered data
- Measurement error / misclassification
- Meta-analysis
- Miscellaneous
- Missing data
- Randomized controlled trials
- Stata
- Survival analysis

### Bayesian inference

- Bayesian inference: are parameters fixed or random?
- My first foray with Stan
- Automatic convergence checking in Bayesian inference with runjags
- 'Monte-Carlo sensitivity analysis' recommended against

### Causal inference

- Potential outcomes, counterfactuals, causal effects, and randomization
- Conditional randomization, standardization, and inverse probability weighting
- Estimating causal effects from observational studies
- Using hazard ratios to estimate causal effects in RCTs
- Estimating effects when outcomes are truncated by death
- Why you shouldn't use propensity score matching

### Inference

- Standard deviation versus standard error
- The miracle of the bootstrap
- The difference between the sample mean and the population mean
- A/B testing and Pearson's chi-squared test of independence
- The t-test and robustness to non-normality
- Wald vs likelihood ratio test
- A/B testing - confidence interval for the difference in proportions using R
- Wilcoxon-Mann-Whitney as an alternative to the t-test
- Adjusting for optimism/overfitting in measures of predictive ability using bootstrapping
- Banning p-values from journals
- On "The fallacy of placing confidence in confidence intervals"
- Frequentists should more often consider using Bayesian methods

### Linear regression

- Assumptions for linear regression
- Regression inference assuming predictors are fixed
- Linear regression with random regressors, part 2
- The robust sandwich variance estimator for linear regression (theory)
- R squared and adjusted R squared
- R squared and goodness of fit in linear regression
- The robust sandwich variance estimator for linear regression (using R)
- Interval regression with heteroskedastic errors
- R squared/correlation depends on variance of predictor

### Logistic regression / Generalized linear models

- R squared in logistic regression
- The Hosmer-Lemeshow goodness of fit test for logistic regression
- Deviance goodness of fit test for Poisson regression
- Area under the ROC curve - assessing discrimination in logistic regression
- Checking functional form in logistic regression using loess plots
- Comparing predictive ability of two nested logistic regression models
- Interpreting odds and odds ratios
- Why shouldn't I use linear regression if my outcome is binary?

### Longitudinal and clustered data

- Robustness of linear mixed models
- Odds ratios, collapsibility, marginal vs. conditional, GEE vs GLMMs

### Measurement error / misclassification

- Adjusting for covariate misclassification in logistic regression - predictive value weighting
- Using Stata's sem to adjust for covariate measurement error

### Meta-analysis

- Fixed versus random-effects meta-analysis - efficiency and confidence interval coverage
- Meta-analysis of last week's Scottish independence polls
- Meta-analysis of Scottish independence polls (update 17th September 2014)
- Prediction intervals after random-effects meta-analysis

### Miscellaneous

- Test for Alzheimer's (allegedly) no better than a coin toss
- A statistician's initial experiences of Git/GitHub
- Prof. Alan Agresti on modelling ordinal data, issues with Wald based inferences, and GEE for ordinal data
- Machine learning vs. traditional modelling techniques
- Running simulations in R using Amazon Web Services

### Missing data

- When is complete case analysis unbiased?
- Multiple imputation with interactions and non-linear terms
- Multiple imputation using random forest
- Missing covariates in structural equation models
- When is complete case/records logistic regression unbiased?
- Including the outcome in imputation models of covariates
- Substantive model compatible imputation of covariates - smcfcs in R
- Multiple imputation followed by deletion of imputed outcomes
- Missing covariates in competing risks analysis
- Weighting after multiple imputation for MNAR sensitivity analysis not recommended
- smcfcs in R - updated version 1.1.1 with critical bug fix
- On the missing at random assumption in longitudinal trials
- Multiple imputation for missing covariates in Poisson regression
- Combining bootstrapping with multiple imputation
- Imputing missing covariates in nested case-control and case cohort studies

### Randomized controlled trials

- Adjusting for baseline covariates in randomized controlled trials
- Leveraging baseline covariates for improved efficiency in randomized controlled trials
- Clustering in randomized controlled trials
- Robustness to misspecification when adjusting for baseline in RCTs
- Is the two sample t-test/ANOVA really biased in RCTs?
- Improving efficiency in RCTs using propensity scores
- Multiarm trials - should we allow for multiplicity?
- Matching analysis to design: stratified randomization in trials
- Estimands and assumptions in clinical trials
- Confidence intervals for the hazard ratio in RCTs which agree with log rank test
- Covariate adjustment and prediction of mean response in randomised trials
- Live stream seminar 26th October 2017: Covariate adjustment and prediction of mean response in randomised trials
- Randomisation as the basis for inference in trials

### Stata

- Stata-Mata's st_view function - use with care!
- Why I think Stata's old xi: prefix is still useful
- Estimating risk ratios from observational data in Stata