Resources

Some useful tools & recommendations

Here's a list of useful tools and links to other resources that I love, and therefore recommend you check out.
I used many of these resources to construct the Foundations course, so if you took the course it's not necessary to review them.
It might, nonetheless, be of interest to the dilligent ones amongst you =).


Tools

GCR Statistics Research Tools
You can use these online tools to guide your study design process, find the right statistical test and calculate sample sizes

The Equator Network
The gateway to the most important research reporting guidelines

2x2 Contingency Table for Diagnostic Studies
Use this excel sheet to calculate prevalence, PPV, NPV, sensitivity, specificity, accuracy, LR+, LR- and posttest probability

2x2 Contingency Table for Intervention Studies
Use this excel sheet to calculate experimental/control event rates, absolute risk reduction, relative risk, odds ratio, and number needed to treat

That's a claim
Online tool to help think critically about health claims. Brilliantly simple. Be sure to check out the 'about health claims' and 'health interventions' sections.


Recommendations

Online Courses

RStudio - Online learning resources
A good overview of useful learning resources by the makers of RStudio.

Datacamp - Data Scientist with R
In this superb online course track you can learn the basics of R programming for research.

Books

Naked Statistics: Stripping the dread from the data - Charles Wheelan
The easiest introduction into statistics, in a funny jacket.

Essential Medical Statistics - B.R. Kirkwood
A good first (theoretical) textbook on medical statistics.

Discovering Statistics using R - Andy Field
A good first (practical) textbook on medical statistics, with the benefit that you will also learn the basics of R.

An Introduction to Statistical Learning - Gareth James
A great intermediate textbook on statistical learning (includes machine learning) with an emphasis on their application.

The Elements of Statistical Learning - Trevor Hastle
A great advanced textbook on statistical learning (includes machine learning).

Regression Modeling Strategies - Frank E. Harrell Jr.
A great advanced textbook on modeling strategies.

Clinical Epidemiology - Diederick E. Grobbee & Arno W. Hoes
A great book on epidemiological concepts and study methodology, written by my former teachers.

The Lady Tasting Tea - David Salzburg
An interesting book (reads like a novel) on the history of medical statistics.

Articles - Collections

Nature Collection - Statistics for Biologist
A collection of great educational articles on statistical topics.

BMJ Collection - Research Methods & Reporting
A collection of great educational articles on statistical/methodological topics.

BMJ Collection - Statistics at Square One
A collection of basic educational articles on statistical topics.

BMJ Collection - Epidemiology for the uninitiated
A collection of basic educational articles on epidemiology topics.

NEJM Collection - The Changing Face of Clinical Trials
A collection of educational reviews on clinical trial methodology.

Lancet Collection - Epidemiology 2002
A collection of educational reviews on statistics/study methodology.

Lancet Collection - Epidemiology 2005
A collection of educational reviews on statistics/study methodology.

Lancet Collection - Increasing value, reducing waste
A collection of great articles on how to avoid common traps of clinical research and how to increase your clinical impact.

Articles - Problems With Current Research

Scientists Rise Up Against Statistical Significance
A recent Nature commentary on the the significance problem.

The ASA Statement on p-Values: Context, Process, and Purpose (2016)
This is the main paper by the American Statistician Association's statement in The American Statistician 2016 to adres the problems around statistical significance in research. Be sure to also checkout the 23 articles in the supplementary material.

The ASA Statement on p-Values: Statistical Inference in the 21st Century: A World Beyond p < 0.05 (2019)
This is the follow-up part of the American Statistician Association's statement in The American Statistician 2019 to adres the problems around statistical significance in research. This supplement contains many relevant articles!

Key Concepts for Making Informed Choices
An insightful Nature commentary on the process of informed decision making

Articles - Clinical Prediction Models

Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): The TRIPOD Statement

Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): Explanation and Elaboration

Diagnostic and prognostic prediction models

Towards better clinical prediction models: seven steps for development and an ABCD for validation

Guide to presenting clinical prediction models for use in clinical settings

Articles - Etiological Research

Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Guidelines for reporting observational studies

Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and elaboration

The Environment and Disease: Association or Causation? - Sir Austin Bradford Hill

Articles - Diagnostic & Reproducibility Research

STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies

Quantifying the Accuracy of a Diagnostic Test or Marker

Quantifying the Added Value of a Diagnostic Test or Marker

Beyond Diagnostic Accuracy: The Clinical Utility of Diagnostic Tests

Sensitivity and Specificity should be De-emphasized in Diagnostic Accuracy Studies

Limitations of Sensitivity, Specificity, Likelihood Ratio, and Bayes' Theorem in Assessing Diagnostic Probabilities: A Clinical Example

Sensitivity, Specificity, and Predictive Values: Foundations, Pliabilities, and Pitfalls in Research and Practice

Reporting and Interpreting Decision Curve Analysis: A Guide for Investigators

Integrating the Predictiveness of a Marker with Its Performance as a Classifier

A review of solutions for diagnostic accuracy studies with an imperfect or missing reference standard

QUADAS-2: A Revised Tool for the Quality Assessment of Diagnostic Accuracy Studies

Guidelines for Reporting Reliability and Agreement Studies (GRRAS) were proposed

Methodological note: Accuracy, precision, and validity

When to use agreement versus reliability measures

Receiver-operating characteristic curve analysis in diagnostic, prognostic and predictive biomarker research

Articles - Prognostic Research

Prognosis Research Strategy (PROGRESS) 1: A framework for researching clinical outcomes

Prognosis Research Strategy (PROGRESS) 2: Prognostic Factor Research

Prognosis Research Strategy (PROGRESS) 3: Prognostic Model Research

Prognosis Research Strategy (PROGRESS) 4: Stratified medicine research

Prognosis and Prognostic Research: Developing a prognostic model

Prognosis and Prognostic Research: Validating a prognostic model

Risk Prediction Models: I. Development, internal validation, and assessing the incremental value of a new (bio)marker

Risk Prediction Models: II. External validation, model updating, and impact assessment.

Articles - Intervention Research

CONSORT 2010 Statement: updated guidelines for reporting parallel group randomised trials

CONSORT 2010 Explanation and Elaboration: updated guidelines for reporting parallel group randomised trials

CONSORT Statement Extensions

Making Sense of Statistics in Clinical Trial Reports - Part 1 of a 4-Part Series on Statistics for Clinical Trials

Statistical Controversies in Reporting of Clinical Trials - Part 2 of a 4-Part Series on Statistics for Clinical Trials

Design of Major Randomized Trials - Part 3 of a 4-Part Series on Statistics for Clinical Trials

Challenging Issues in Clinical Trial Design - Part 4 of a 4-Part Series on Statistics for Clinical Trials

Through the looking glass: understanding non-inferiority

Adaptive designs: The Swiss Army knife among clinical trial designs?

Improved Designs for Cluster Randomized Trials” design

Rethinking pragmatic randomised controlled trials: introducing the “cohort multiple randomised controlled trial” design