Triangulation in aetiological epidemiology
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[1] D. Lawlor,et al. Cohort Profile: The ‘Children of the 90s’—the index offspring of the Avon Longitudinal Study of Parents and Children , 2012, International journal of epidemiology.
[2] J. Morris,et al. Uses of Epidemiology* , 1955, British medical journal.
[3] Gordon Thallon Stewart. Trends in epidemiology: application to health service research and training , 1972 .
[4] N J Wald,et al. Use of blood pressure lowering drugs in the prevention of cardiovascular disease: meta-analysis of 147 randomised trials in the context of expectations from prospective epidemiological studies , 2009, BMJ : British Medical Journal.
[5] Yoav Ben-Shlomo,et al. Model Selection of the Effect of Binary Exposures over the Life Course , 2015, Epidemiology.
[6] D. Lawlor,et al. Clustered Environments and Randomized Genes: A Fundamental Distinction between Conventional and Genetic Epidemiology , 2007, PLoS medicine.
[7] Ezra Susser,et al. Commentary: Advent of sibling designs. , 2011, International journal of epidemiology.
[8] Martin McKee,et al. Reductions in the United Kingdom's Government Housing Benefit and Symptoms of Depression in Low-Income Households , 2016, American journal of epidemiology.
[9] J. Horwood. UK Biobank Data: Come and Get It , 2014 .
[10] Nancy Krieger,et al. The tale wagged by the DAG: broadening the scope of causal inference and explanation for epidemiology. , 2016, International journal of epidemiology.
[11] Richard M Martin,et al. Effects of promoting longer-term and exclusive breastfeeding on adiposity and insulin-like growth factor-I at age 11.5 years: a randomized trial. , 2013, JAMA.
[12] B. Shipley. Cause and Correlation in Biology by Bill Shipley , 2016 .
[13] R. Collins,et al. Age-specific relevance of usual blood pressure to vascular mortality: a meta-analysis of individual data for one million adults in 61 prospective studies , 2002, The Lancet.
[14] M. Susser. Causal Thinking in the Health Sciences: Concepts and Strategies in Epidemiology , 1973 .
[15] K. Straif,et al. Body Fatness and Cancer--Viewpoint of the IARC Working Group. , 2016, The New England journal of medicine.
[16] Charles Bricker,et al. A history of cartography : 2500 years of maps and mapmakers , 1969 .
[17] John Keay,et al. The Great Arc: The Dramatic Tale of How India Was Mapped and Everest Was Named , 2000 .
[18] Brian A Ference,et al. Clinical Effect of Naturally Random Allocation to Lower Systolic Blood Pressure Beginning Before the Development of Hypertension , 2014, Hypertension.
[19] Michael W. Varner,et al. A Multicenter, Randomized Trial of Treatment for Mild Gestational Diabetes , 2010 .
[20] J. Danesh,et al. Large-scale association analysis identifies new risk loci for coronary artery disease , 2013 .
[21] Alex Broadbent,et al. Causality and causal inference in epidemiology: the need for a pluralistic approach , 2016, International journal of epidemiology.
[22] Sandra Mathison,et al. Why Triangulate? , 1988 .
[23] Gita D Mishra,et al. Theoretical underpinning for the use of sibling studies in life course epidemiology , 2009 .
[24] P W Callas,et al. Cancer case-control studies with other cancers as controls. , 1988, International journal of epidemiology.
[25] C. Sudlow,et al. UK Biobank Data: Come and Get It , 2014, Science Translational Medicine.
[26] G. Davey Smith,et al. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression , 2015, International journal of epidemiology.
[27] G. Davey Smith,et al. Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator , 2016, Genetic epidemiology.
[28] Anna C. Balazs,et al. Influence of adherence to treatment and response of cholesterol on mortality in the coronary drug project. , 1980, The New England journal of medicine.
[29] Richard M Martin,et al. The effect of breastfeeding on mean body mass index throughout life: a quantitative review of published and unpublished observational evidence. , 2005, The American journal of clinical nutrition.
[30] Tom R. Gaunt,et al. Genetic Variants in Novel Pathways Influence Blood Pressure and Cardiovascular Disease Risk , 2011, Nature.
[31] Stephen R Cole,et al. Assessment and indirect adjustment for confounding by smoking in cohort studies using relative hazards models. , 2014, American journal of epidemiology.
[32] Stijn Vansteelandt,et al. Commentary: The formal approach to quantitative causal inference in epidemiology: misguided or misrepresented? , 2016, International journal of epidemiology.
[33] Ezra Susser,et al. Invited commentary: The use of sibship studies to detect familial confounding. , 2010, American journal of epidemiology.
[34] J Siemiatycki,et al. Associations between cigarette smoking and each of 21 types of cancer: a multi-site case-control study. , 1995, International journal of epidemiology.
[35] Uwe Flick,et al. Triangulation Revisited: Strategy of Validation or Alternative? , 1992 .
[36] Arvid Sjölander,et al. Sibling comparison designs: bias from non-shared confounders and measurement error. , 2012, Epidemiology.
[37] Debbie A Lawlor,et al. The Society for Social Medicine John Pemberton Lecture 2011. Developmental overnutrition--an old hypothesis with new importance? , 2013, International journal of epidemiology.
[38] Shah Ebrahim,et al. Observational versus randomised trial evidence , 2004, The Lancet.
[39] Paolo Boffetta,et al. Exposure to diesel and gasoline engine emissions and the risk of lung cancer. , 2006, American journal of epidemiology.
[40] G. Davey Smith,et al. Mendelian randomization: genetic anchors for causal inference in epidemiological studies , 2014, Human molecular genetics.
[41] Jay S. Kaufman,et al. Methods in social epidemiology , 2006 .
[42] George Davey Smith,et al. Negative control exposures in epidemiologic studies. , 2012, Epidemiology.
[43] M. Hammersley. Troubles with triangulation , 2008 .
[44] Francis Sullivan. Our Mathematical Universe: My Quest for the Ultimate Nature of Reality , 2014 .
[45] Samir Okasha,et al. A Companion to the Philosophy of Science , 2000 .
[46] Debbie A Lawlor,et al. Association between hyperglycaemia and adverse perinatal outcomes in south Asian and white British women: analysis of data from the Born in Bradford cohort , 2015, The lancet. Diabetes & endocrinology.
[47] S. Reilly,et al. Improved estimates of the benefits of breastfeeding using sibling comparisons to reduce selection bias. , 2005, Health services research.
[48] C. Teddlie,et al. SAGE Handbook of Mixed Methods in Social & Behavioral Research , 2010 .
[49] Charles Kooperberg,et al. Risks and benefits of estrogen plus progestin in healthy postmenopausal women: principal results From the Women's Health Initiative randomized controlled trial. , 2002, JAMA.
[50] Jane Wardle,et al. Effect of a behavioural intervention in obese pregnant women (the UPBEAT study): a multicentre, randomised controlled trial. , 2015, The lancet. Diabetes & endocrinology.
[51] M. Graffar. [Modern epidemiology]. , 1971, Bruxelles medical.
[52] Gita D. Mishra,et al. Family matters: designing, analysing and understanding family based studies in life course epidemiology , 2009 .
[53] G. Smith. Assessing intrauterine influences on offspring health outcomes: can epidemiological studies yield robust findings? , 2008, Basic & clinical pharmacology & toxicology.
[54] David J. C. MacKay,et al. Information Theory, Inference, and Learning Algorithms , 2004, IEEE Transactions on Information Theory.
[55] Sander Greenland,et al. An introduction to instrumental variables for epidemiologists. , 2018, International journal of epidemiology.
[56] Per Gustavsson,et al. IARC Monographs: 40 Years of Evaluating Carcinogenic Hazards to Humans , 2015, Environmental health perspectives.
[57] Model Comparison and Occam ’ s Razor , 2022 .
[58] Eric Tchetgen Tchetgen,et al. The Control Outcome Calibration Approach for Causal Inference With Unobserved Confounding , 2013, American journal of epidemiology.
[59] C. Furberg,et al. How should one analyse and interpret clinical trials in which patients don't take the treatments assigned to them? , 2010, Journal of the Royal Society of Medicine.
[60] N. Pearce,et al. Critical discussion in epidemiology: problems with the Popperian approach. , 1989, Journal of clinical epidemiology.
[61] Rebecca Hardy,et al. A structured approach to hypotheses involving continuous exposures over the life course , 2016, International journal of epidemiology.
[62] Debbie A Lawlor,et al. Cohort Profile: the Born in Bradford multi-ethnic family cohort study. , 2013, International journal of epidemiology.
[63] Susan R. Johnson,et al. Effects of Estrogen or Estrogen/ Progestin Regimens on Heart Disease Risk Factors in Postmenopausal Women: The Postmenopausal Estrogen/Progestin Interventions (PEPI) Trial , 1995 .
[64] James M. Robins,et al. Observational Studies Analyzed Like Randomized Experiments: An Application to Postmenopausal Hormone Therapy and Coronary Heart Disease , 2008, Epidemiology.
[65] D. Lawlor. Commentary: Two-sample Mendelian randomization: opportunities and challenges , 2016, International journal of epidemiology.
[66] David E Newby,et al. Effect of metformin on maternal and fetal outcomes in obese pregnant women (EMPOWaR): a randomised, double-blind, placebo-controlled trial , 2015, The lancet. Diabetes & endocrinology.
[67] Katherine M Keyes,et al. On sibling designs. , 2013, Epidemiology.
[68] Marie-Jo Brion,et al. Association of Maternal Weight Gain in Pregnancy With Offspring Obesity and Metabolic and Vascular Traits in Childhood , 2010, Circulation.
[69] S. Ebrahim,et al. 'Mendelian randomization': can genetic epidemiology contribute to understanding environmental determinants of disease? , 2003, International journal of epidemiology.
[70] Penny Gordon-Larsen,et al. Are Adolescents Who Were Breast-fed Less Likely to Be Overweight?: Analyses of Sibling Pairs to Reduce Confounding , 2005, Epidemiology.
[71] M. Lipsitch,et al. Negative Controls: A Tool for Detecting Confounding and Bias in Observational Studies , 2010, Epidemiology.
[72] A. B. Hill. The Environment and Disease: Association or Causation? , 1965, Proceedings of the Royal Society of Medicine.
[73] Tom M Palmer,et al. Genetic Evidence for Causal Relationships Between Maternal Obesity-Related Traits and Birth Weight. , 2016, JAMA.
[74] Debbie A Lawlor,et al. What are the causal effects of breastfeeding on IQ, obesity and blood pressure? Evidence from comparing high-income with middle-income cohorts , 2011, International journal of epidemiology.
[75] Alun D. Hughes,et al. Metabolomic Profiling of Statin Use and Genetic Inhibition of HMG-CoA Reductase , 2016, Journal of the American College of Cardiology.
[76] D. Lawlor,et al. Cohort Profile: The Avon Longitudinal Study of Parents and Children: ALSPAC mothers cohort , 2012, International journal of epidemiology.
[77] Richard M Martin,et al. Effects of prolonged and exclusive breastfeeding on child height, weight, adiposity, and blood pressure at age 6.5 y: evidence from a large randomized trial. , 2007, The American journal of clinical nutrition.
[78] Manfred Max Bergman,et al. Advances in mixed methods research , 2008 .
[79] T. McDade,et al. Breastfeeding as obesity prevention in the United States: A sibling difference model , 2010, American journal of human biology : the official journal of the Human Biology Council.
[80] George Davey Smith,et al. Mendelian randomization: Using genes as instruments for making causal inferences in epidemiology , 2008, Statistics in medicine.