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Uber stats nerd

Statistician

eam

Biography

I am a statistician working in the pharmaceutical industry. Interests include Bayesian statistics, graphics, modelling, prediction particularly in the clinical realm.

Interests

  • Using R for statistical analysis
  • Statistical Graphics
  • Bayesian Analysis
  • Reproducible reporting
  • Study design simulation with R

Education

  • MSc in Medical Statistics, 2004

    London School of Hygiene and Tropical Medicine

Shiny Apps & Analyses

R Shiny application examples and reproducible analyses using R Markdown to bring data to life. Click on the blue menu ‘R Shiny’ button to see the Shiny apps. The ‘Other’ option displays all non-R shiny analyses. Explore the Git repository for more…

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Gamma Poisson edification

The gamma Poisson PMF

Analysing method comparison experiments

Mixed model analysis of technical replicates

Play Your Cards Right

Using flexdashboard to solve a puzzle

Planning a survival analysis study

Using the exponential distribution

Missing data Under construction

Dealing with missing data in statistical analyses

Time to event analyses

Semiparametric and parametric time to event modelling

Transform your data lite

Investigating transformations and fitting linear models

Transform your data

Investigating transformations and fitting linear models

Covariate adjustment RCTs

Investigating adjusting for covariates in parallel RCTs when the response is binary

Covariate adjustment RCTs

Investigating adjusting for covariates in RCTs when the response is continuous

Under construction

Mixed model with longitudinal response

PLOTTING THE EVOLUTION OF A MEASUREMENT AND ESTIMATING SUMMARY STATISTICS (REVISITED)

Plotting longitudinal data and estimating means with the help of a natural log transformation revisited

Using GLS for treatment effect estimation

Estimating treatment effects with a longitudinal RCT

Limit of detection estimation in the presence of censored observations

Calculating limits of detection for qPCR assays

The variation of a variance

Inference about a population variance

A test of interaction is necessary

Differential treatment effects

If the response is ordinal, respect it

The proportional odds model

Visualizing probability density functions

Visualizing probability density functions commonly used for Bayesian logistic regression

Looking for those elusive responders (and non responders)

Random variation (‘the magic had of chance’) is very likely to lead to observing responders and non responders in a …

One Way ANOVA Power

Power simulation for one way analysis of variance

BOXPLOTS ON TRANSFORMED DATA

Boxplots can hide a lot of information

SIMPLE HORIZONTAL BAR PLOT

Nothing more, nothing less

ANALYSING LONGITUDINAL DATA - RANDOM EFFECTS

Simulating allows us to play God. With divine insight we know the true data generating mechanism.

One Way ANOVA

Why analyse variances (ANOVA) when interest is in differences in population means?

CROSSOVER STUDY RELATED ANALYSES

A number of cross over trial related analyses

EXPLORING ANCOVA ANALYSIS

The analysis of an RCT based on a continuous endpoint that is log-normal distributed

FDA POPULATION BIOEQUIVALENCE (PBE) STATISTICAL ANALYSIS PROCEDURE

Using R we explore the ‘FDA PBE Statistical Analysis Procedure Used in Bioequivalence Determination of Budesonide’

GAMBLER’S RUIN, A CURIOUS COIN FLIPPING GAME

A game where gamblers simultaneously flip a single coin…

GLS MODELLING OF LONGITUDINAL RCT

Estimating treatment effect with patients followed over time.

IDENTIFYING RESPONDERS AND NON RESPONDERS IN A RCT?

A simulation of a RCT demonstrating why it is wrong to analyse arms of a trial separately to identify responders and non responders.

PIERRE REMOND DE MONTMORT’S MATCHING PROBLEM 1708

The biggest coincidence of all would be if there were no coincidences.

PLOTTING THE EVOLUTION OF A MEASUREMENT TAKEN ON A COHORT AND ESTIMATING SUMMARY STATISTICS

Plotting longitudinal data and estimating means with the help of a natural log transformation

RCT ADJUSTING FOR COVARIATES

Investigation of adjusted and unadjusted power in the setting of RCT when there is a predictive biomarker

SIMULATE A 3 LEVEL NESTED EXPERIMENT

Simulating balanced or unbalanced nested study design, plotting and a variance components analysis

SIMULATE, PLOT AND ANALYSE A 3 LEVEL NESTED STUDY

Simulating a 3 level nested study design, plotting and variance components analysis

SIMULATING, PLOTTING AND ANALYSING A TWO PERIOD CROSSOVER TRIAL

Investigating a crossover trial, a longitudinal study in which subjects receive a sequence of different treatments

WHEN THE SAMPLE SIZE IS TWO, A 50% CONFIDENCE INTERVAL IS DEFINED BY THE TWO VALUES

Two data points may convey more information than you think

EXPLORING THE LOG-NORMAL DISTRIBUTION

Sample size/power for an RCT based on a continuous biomarker endpoint that is log-normal distributed

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