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ssrn.4611295

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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1001/jama.2020.1267openalex-extracted

Why Test for Proportional Hazards?

inferredcites →https://doi.org/10.1001/jama.2020.13601openalex-extracted

Precision Nutrition—the Answer to “What to Eat to Stay Healthy”

inferredcites →https://doi.org/10.1007/s10654-019-00487-5openalex-extracted

Unreformed nutritional epidemiology: a lamp post in the dark forest

inferredcites →https://doi.org/10.1016/j.compbiomed.2021.104365openalex-extracted

Precision nutrition: A systematic literature review

inferredcites →https://doi.org/10.1016/j.jand.2019.06.010openalex-extracted

Best Practices for Conducting and Interpreting Studies to Validate Self-Report Dietary Assessment Methods

inferredcites →https://doi.org/10.1016/j.jclinepi.2015.05.029openalex-extracted

Assessment of vibration of effects due to model specification can demonstrate the instability of observational associations

inferredcites →https://doi.org/10.1016/j.neuroimage.2021.118502openalex-extracted

Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?

inferredcites →https://doi.org/10.1016/s0140-6736(07)61602-xopenalex-extracted

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

inferredcites →https://doi.org/10.1017/s002966510800712xopenalex-extracted

The Second World Cancer Research Fund/American Institute for Cancer Research Expert Report. Food, Nutrition, Physical Activity, and the Prevention of Cancer: A Global Perspective

inferredcites →https://doi.org/10.1017/s0029665122000775openalex-extracted

Interpretation of observational studies: the good, the bad and the sensational

inferredcites →https://doi.org/10.1037/bul0000220openalex-extracted

Crowdsourcing hypothesis tests: Making transparent how design choices shape research results.

inferredcites →https://doi.org/10.1038/ejcn.2013.59openalex-extracted

Meat consumption and diet quality and mortality in NHANES III

inferredcites →https://doi.org/10.1038/s41562-018-0506-1openalex-extracted

The association between adolescent well-being and digital technology use

inferredcites →https://doi.org/10.1038/s41562-020-0912-zopenalex-extracted

Specification curve analysis

inferredcites →https://doi.org/10.1073/pnas.2203150119openalex-extracted

Observing many researchers using the same data and hypothesis reveals a hidden universe of uncertainty

inferredcites →https://doi.org/10.1080/00031305.2019.1565553openalex-extracted

Multiple Perspectives on Inference for Two Simple Statistical Scenarios

inferredcites →https://doi.org/10.1093/ajcn/65.4.1220sopenalex-extracted

Adjustment for total energy intake in epidemiologic studies

inferredcites →https://doi.org/10.1093/ajcn/nqab002openalex-extracted

Characteristics and quality of systematic reviews and meta-analyses of observational nutritional epidemiology: a cross-sectional study

inferredcites →https://doi.org/10.1093/ajcn/nqab266openalex-extracted

Adjustment for energy intake in nutritional research: a causal inference perspective

inferredcites →https://doi.org/10.1093/ajcn/nqac114openalex-extracted

Re: Adjustment for energy intake in nutritional research: a causal inference perspective

inferredcites →https://doi.org/10.1093/ajcn/nqac188openalex-extracted

Theory and performance of substitution models for estimating relative causal effects in nutritional epidemiology

inferredcites →https://doi.org/10.1093/aje/kwi038openalex-extracted

Associations of Dietary Protein with Disease and Mortality in a Prospective Study of Postmenopausal Women

inferredcites →https://doi.org/10.1093/cdn/nzz104openalex-extracted

Methods for the Selection of Covariates in Nutritional Epidemiology Studies: A Meta-Epidemiological Review

inferredcites →https://doi.org/10.1093/ije/dyz271openalex-extracted

Vibration of effects in epidemiologic studies of alcohol consumption and breast cancer risk

inferredcites →https://doi.org/10.1126/science.aba3807openalex-extracted

Challenges of human nutrition research

inferredcites →https://doi.org/10.1136/bmj.i1981openalex-extracted

Sparse data bias: a problem hiding in plain sight

inferredcites →https://doi.org/10.1146/annurev-nutr-061021-025153openalex-extracted

Precision Nutrition: The Hype Is Exceeding the Science and Evidentiary Standards Needed to Inform Public Health Recommendations for Prevention of Chronic Disease

inferredcites →https://doi.org/10.1146/annurev-nutr-082018-124610openalex-extracted

Evidence Collection and Evaluation for the Development of Dietary Guidelines and Public Policy on Nutrition

inferredcites →https://doi.org/10.1177/0049124194023002004openalex-extracted

Sampling Weights and Regression Analysis

inferredcites →https://doi.org/10.1177/0956797617723726openalex-extracted

Probing Birth-Order Effects on Narrow Traits Using Specification-Curve Analysis

inferredcites →https://doi.org/10.1177/1745691616658637openalex-extracted

Increasing Transparency Through a Multiverse Analysis

inferredcites →https://doi.org/10.1177/2515245917747646openalex-extracted

Many Analysts, One Data Set: Making Transparent How Variations in Analytic Choices Affect Results

inferredcites →https://doi.org/10.1186/s12874-020-0914-6openalex-extracted

Evaluation of confounding in epidemiologic studies assessing alcohol consumption on the risk of ischemic heart disease

inferredcites →https://doi.org/10.1186/s12916-018-1122-7openalex-extracted

From hype to reality: data science enabling personalized medicine

inferredcites →https://doi.org/10.1186/s13643-017-0422-xopenalex-extracted

Comparison of two independent systematic reviews of trials of recombinant human bone morphogenetic protein-2 (rhBMP-2): the Yale Open Data Access Medtronic Project

inferredcites →https://doi.org/10.1214/088342306000000691openalex-extracted

Struggles with Survey Weighting and Regression Modeling

inferredcites →https://doi.org/10.1371/journal.pbio.3001398openalex-extracted

Leveraging vibration of effects analysis for robust discovery in observational biomedical data science

inferredcites →https://doi.org/10.2105/ajph.2016.303314openalex-extracted

Contribution of the Nurses’ Health Studies to Uncovering Risk Factors for Type 2 Diabetes: Diet, Lifestyle, Biomarkers, and Genetics

inferredcites →https://doi.org/10.3390/nu14235164openalex-extracted

A Meta-Epidemiological Study of Positive Results in Clinical Nutrition Research: The Good, the Bad and the Ugly of Statistically Significant Findings

inferredcites →https://doi.org/10.3402/ijch.v71i0.18537openalex-extracted

A traditional Sami diet score as a determinant of mortality in a general northern Swedish population

inferredcites →https://doi.org/10.3945/ajcn.112.047142openalex-extracted

Is everything we eat associated with cancer? A systematic cookbook review

inferredcites →https://doi.org/10.3945/an.115.009258openalex-extracted

Update on NHANES Dietary Data: Focus on Collection, Release, Analytical Considerations, and Uses to Inform Public Policy

inferredcites →https://doi.org/10.3945/jn.115.219634openalex-extracted

Addressing Current Criticism Regarding the Value of Self-Report Dietary Data

inferredcites →https://doi.org/10.7326/l20-0070openalex-extracted

Red and Processed Meat Consumption and Risk for All-Cause Mortality and Cardiometabolic Outcomes

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