Nan M. Laird

96.9k total citations · 16 hit papers
240 papers, 68.9k citations indexed

About

Nan M. Laird is a scholar working on Statistics and Probability, Genetics and Molecular Biology. According to data from OpenAlex, Nan M. Laird has authored 240 papers receiving a total of 68.9k indexed citations (citations by other indexed papers that have themselves been cited), including 91 papers in Statistics and Probability, 72 papers in Genetics and 25 papers in Molecular Biology. Recurrent topics in Nan M. Laird's work include Statistical Methods and Bayesian Inference (65 papers), Genetic Associations and Epidemiology (64 papers) and Statistical Methods and Inference (34 papers). Nan M. Laird is often cited by papers focused on Statistical Methods and Bayesian Inference (65 papers), Genetic Associations and Epidemiology (64 papers) and Statistical Methods and Inference (34 papers). Nan M. Laird collaborates with scholars based in United States, United Kingdom and Germany. Nan M. Laird's co-authors include Rebecca DerSimonian, James H. Ware, Garrett M. Fitzmaurice, Steve Horvath, Xin Xu, Christoph Lange, Ann G. Lawthers, Liesi E. Hebert, Paul C. Weiler and Joseph P. Newhouse and has published in prestigious journals such as Science, New England Journal of Medicine and Proceedings of the National Academy of Sciences.

In The Last Decade

Nan M. Laird

236 papers receiving 66.5k citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Meta-analysis in clinical trials

1986 32.8k citations Nan M. Laird et al. profile →
Random-Effects Models for Longitudinal Data

1982 6.8k citations Nan M. Laird et al. profile →
Applied Longitudinal Analysis

2011 2.9k citations Nan M. Laird et al. profile →
The Nature of Adverse Events in Hospitalized Patients

1991 2.7k citations Nan M. Laird et al. profile →
Meta-analysis in clinical trials revisited

2015 2.0k citations Nan M. Laird et al. profile →
Impact of Overweight on the Risk of Developing Common Chronic Diseases During a 10-Year Period

2001 1.3k citations Nan M. Laird et al. profile →
Reducing obesity via a school-based interdisciplinary intervention among youth: Planet Health.

1999 1.0k citations Arthur M. Sobol, Nan M. Laird et al. profile →
Using the general linear mixed model to analyse unbalanced repeated measures and longitudinal data

1997 1.0k citations Nan M. Laird et al. profile →
Implementing a unified approach to family-based tests of association

2000 693 citations Nan M. Laird, Xin Xu et al. Genetic Epidemiology profile →
The family based association test method: strategies for studying general genotype–phenotype associations

2001 606 citations Xin Xu, Nan M. Laird et al. profile →
Random-Effects Models for Serial Observations with Binary Response

1984 535 citations Nan M. Laird et al. profile →
Relation between Malpractice Claims and Adverse Events Due to Negligence

1991 521 citations Nan M. Laird et al. profile →
Nonparametric Maximum Likelihood Estimation of a Mixing Distribution

1978 519 citations Nan M. Laird Journal of the American Statistical Association profile →
Alpha-2 macroglobulin is genetically associated with Alzheimer disease

1998 518 citations Nan M. Laird, Rudolph E. Tanzi et al. profile →
Missing data in longitudinal studies

1988 505 citations Nan M. Laird profile →
A Unified Approach to Adjusting Association Tests for Population Admixture with Arbitrary Pedigree Structure and Arbitrary Missing Marker Information

2000 504 citations Nan M. Laird et al. profile →

Peers

Countries citing papers authored by Nan M. Laird

Since Specialization

Citations

This map shows the geographic impact of Nan M. Laird's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Nan M. Laird with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nan M. Laird more than expected).

Fields of papers citing papers by Nan M. Laird

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nan M. Laird. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Nan M. Laird. The network helps show where Nan M. Laird may publish in the future.

Co-authorship network of co-authors of Nan M. Laird

This figure shows the co-authorship network connecting the top 25 collaborators of Nan M. Laird. A scholar is included among the top collaborators of Nan M. Laird based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Nan M. Laird. Nan M. Laird is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work	Indexed citations
1	Fallacies and Pitfalls in Genome-Wide Association Studies 2023 ·Julian Hecker, (unknown), Andrew Hughes, Julie Neidich, Carl Taswell, Nan M. Laird	1
2	Region-based analysis of rare genomic variants in whole-genome sequencing datasets reveal two novel Alzheimer’s disease-associated genes: DTNB and DLG2 2022 ·Molecular Psychiatry ·Dmitry Prokopenko, Sanghun Lee, Julian Hecker, Kristina Mullin, Sarah Morgan, Yuriko Katsumata, (unknown), Michael W. Weiner, David W. Fardo, Nan M. Laird, Lars Bertram, (unknown), Christoph Lange, Rudolph E. Tanzi	16
3	A unifying framework for rare variant association testing in family-based designs, including higher criticism approaches, SKATs, and burden tests 2020 ·Bioinformatics ·Julian Hecker, F. William Townes, Priyadarshini Kachroo, Cecelia Laurie, Jessica Lasky‐Su, John Ziniti, Michael H. Cho, Scott T. Weiss, Nan M. Laird, Christoph Lange	5
4	A comparison of popular TDT‐generalizations for family‐based association analysis 2019 ·Genetic Epidemiology ·Julian Hecker, Nan M. Laird, Christoph Lange	3
5	Family‐based tests for associating haplotypes with general phenotype data 2017 ·Genetic Epidemiology ·Julian Hecker, Xin Xu, F. William Townes, Heide Fier, Chris Corcoran, Nan M. Laird, Christoph Lange	3
6	Genome-Wide Association Study of the Genetic Determinants of Emphysema Distribution 2016 ·American Journal of Respiratory and Critical Care Medicine ·Adel Boueiz, Sharon M. Lutz, Michael H. Cho, Craig P. Hersh, Russell P. Bowler, George R. Washko, Eitan Halper‐Stromberg, Per Bakke, Amund Gulsvik, Nan M. Laird, Terri H. Beaty, Harvey O. Coxson, James D. Crapo, Edwin K. Silverman, Peter J. Castaldi, Dawn L. DeMeo	37
7	A Genome-Wide Association Study of Emphysema and Airway Quantitative Imaging Phenotypes 2015 ·American Journal of Respiratory and Critical Care Medicine ·Michael H. Cho, Peter J. Castaldi, Craig P. Hersh, Brian D. Hobbs, R. Graham Barr, Ruth Tal‐Singer, Per Bakke, Amund Gulsvik, Raúl San Jośe Estépar, Edwin J.R. van Beek, Harvey O. Coxson, David A. Lynch, George R. Washko, Nan M. Laird, James D. Crapo, Terri H. Beaty, Edwin K. Silverman	97
8	Heritability of Chronic Obstructive Pulmonary Disease and Related Phenotypes in Smokers 2013 ·American Journal of Respiratory and Critical Care Medicine ·Jin Zhou, Michael H. Cho, Peter J. Castaldi, Craig P. Hersh, Edwin K. Silverman, Nan M. Laird	84
9	The Association of Genome-Wide Significant Spirometric Loci with Chronic Obstructive Pulmonary Disease Susceptibility 2011 ·American Journal of Respiratory Cell and Molecular Biology ·Peter J. Castaldi, Michael H. Cho, Augusto A. Litonjua, Per Bakke, Amund Gulsvik, David A. Lomas, W. J. Anderson, Terri H. Beaty, John E. Hokanson, James D. Crapo, Nan M. Laird, Edwin K. Silverman	66
10	On the Optimal Design of Genetic Variant Discovery Studies 2010 ·Statistical Applications in Genetics and Molecular Biology ·Iuliana Ionita‐Laza, Nan M. Laird	12
11	Estimating the Prevalence of Disease Using Relatives of Case and Control Probands 2007 ·Collection of Biostatistics Research Archive ·Kristin N. Javaras, Nan M. Laird, James I. Hudson, B. D. Ripley	2
12	An efficient family‐based association test using multiple markers 2006 ·Genetic Epidemiology ·Xin Xu, Cyril Rakovski, Xiping Xu, Nan M. Laird	34
13	Power estimation of multiple SNP association test of case‐control study and application 2003 ·Genetic Epidemiology ·Ke Hao, Xin Xu, Nan M. Laird, Xiaobin Wang, Xiping Xu	29
14	Self-disparagement as feature and forerunner of depression: Findings from the Stirling County Study 2002 ·Comprehensive Psychiatry ·Jane M. Murphy, Andrew A. Nierenberg, Richard R. Monson, Nan M. Laird, Arthur M. Sobol, Alexander H. Leighton	23
15	Multiple Imputation in Mixture Models for Nonignorable Nonresponse with Follow-ups 1993 ·Journal of the American Statistical Association ·Robert J. Glynn, Nan M. Laird, Donald B. Rubin	89
16	Regression Analysis for Categorical Variables with Outcome Subject to Nonignorable Nonresponse 1988 ·Journal of the American Statistical Association ·Stuart G. Baker, Nan M. Laird	168
17	Maximum Likelihood Computations with Repeated Measures: Application of the EM Algorithm 1987 ·Journal of the American Statistical Association ·Nan M. Laird, Nicholas Lange, Daniel O. Stram	290
18	Empirical Bayes Confidence Intervals Based on Bootstrap Samples 1987 ·Journal of the American Statistical Association ·Nan M. Laird, Thomas A. Louis	164
19	A Reanalysis of the Stanford Heart Transplant Data 1983 ·Journal of the American Statistical Association ·Murray Aitkin, Nan M. Laird, Brian Francis	72
20	Nonparametric Maximum Likelihood Estimation of a Mixing Distribution breakdown → 1978 ·Journal of the American Statistical Association ·Nan M. Laird	519

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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