Tra My Pham

United Kingdom

Research Interests

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Professors in United Kingdom Professors in Biostatistics Biostatistics professors in United Kingdom

Articles (14)

Year:

2024

Year:

2024

For simulation studies that evaluate methods of handling missing data, we argue that generating partially observed data by fixing the complete data and repeatedly simulating the missingness indicators is a superficially attractive idea but only rarely appropriate to use.

Year:

2023

Year:

2023

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2021

Year:

2021

Collaborators (6)

Kingshuk Pal

University College London

UNITED KINGDOM

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Gordon Forbes

King’s College London

UNITED KINGDOM

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Ruth L Goodall

University College London

UNITED KINGDOM

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Ian White

Professor at Institute of Clinical Trials and Methodology (ICTM)

University College London

UNITED KINGDOM

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Jonathan Bartlett

Professor in Medical Statistics

London School of Hygiene & Tropical Medicine

UNITED KINGDOM

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Patrick Phillips

Assistant Professor

University of California, San Francisco

UNITED STATES

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Tra My Pham

Research Interests

Explore related searches

Articles (14)

How to check a simulation study

Missing data: Issues, concepts, methods

Comment on Oberman & Vink: Should we fix or simulate the complete data in simulation studies evaluating missing data methods?

The marginality principle revisited: Should “higher‐order” terms always be accompanied by “lower‐order” terms in regression analyses?

Rethinking intercurrent events in defining estimands for tuberculosis trials

Missing data, part 7. Pitfalls in doing multiple imputation

Missing data, part 6. Choices in doing multiple imputation

Missing data, part 5. Introduction to multiple imputation

Missing data, part 4. Missing data in the outcomes vs in the covariates

Missing data, part 3. How to explore missing data

Missing data, part 2. Missing data mechanisms: Missing completely at random, missing at random, missing not at random, and why they matter

Missing data, part 1. Why missing data are a problem

Cardiovascular outcomes of type 2 diabetic patients treated with DPP‑4 inhibitors versus sulphonylureas as add-on to metformin in clinical practice

A comparison of methods for analyzing a binary composite endpoint with partially observed components in randomized controlled trials

Collaborators (6)

Kingshuk Pal

Gordon Forbes

Ruth L Goodall

Ian White

Jonathan Bartlett

Patrick Phillips

Make your next move.

Tra My Pham

Research Interests

Explore related searches

Articles (14)

How to check a simulation study

Missing data: Issues, concepts, methods

Comment on Oberman &amp; Vink: Should we fix or simulate the complete data in simulation studies evaluating missing data methods?

The marginality principle revisited: Should “higher‐order” terms always be accompanied by “lower‐order” terms in regression analyses?

Rethinking intercurrent events in defining estimands for tuberculosis trials

Missing data, part 7. Pitfalls in doing multiple imputation

Missing data, part 6. Choices in doing multiple imputation

Missing data, part 5. Introduction to multiple imputation

Missing data, part 4. Missing data in the outcomes vs in the covariates

Missing data, part 3. How to explore missing data

Missing data, part 2. Missing data mechanisms: Missing completely at random, missing at random, missing not at random, and why they matter

Missing data, part 1. Why missing data are a problem

Cardiovascular outcomes of type 2 diabetic patients treated with DPP‑4 inhibitors versus sulphonylureas as add-on to metformin in clinical practice

A comparison of methods for analyzing a binary composite endpoint with partially observed components in randomized controlled trials

Collaborators (6)

Kingshuk Pal

Gordon Forbes

Ruth L Goodall

Ian White

Jonathan Bartlett

Patrick Phillips

Make your next move.

Comment on Oberman & Vink: Should we fix or simulate the complete data in simulation studies evaluating missing data methods?