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Introduction to Study Designs and Biostatistics

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Introduction to Study Designs and Biostatistics 4/12/2013 WH RESEARCH TRAINING WORKSHOP 2013 Date: Thursdays ,12:30-1:30pm Venue: Auditorium Western Centre for Health Research & Education Sunshine Hospital Workshop Topic Presenters Date Research Ethics & Governance Dr Tam Nguyen 14-Feb-13 Introduction to Clinical Research Dr Harin Karunajeewa 28-Feb-13 Evaluating the literature A/Professor Kerrie Sanders 14-Mar-13 Writing a research proposal Dr Lizzie Skinner 28-Mar-13 Beginners statistics: Study Design Professor Danny Liew 11-Apr-13 Referencing and EndNote Dr Tam Nguyen & Lynn Higgins 24-Apr-13 Mixed Methods: Quantitative & Qualitative Professor Terrence McCann 9-May-13 Using Excel for research Dr Lizzie Skinner 23-May-13 Making sense of your results Professor Danny Liew 6-Jun-13 Getting your work published A/Professor Kerrie Sanders 20-Jun-13 Writing Abstract for Research Week/ Conferences Dr Debra Kerr 4-Jul-13 Introduction to Study Designs and Biostatistics Danny Liew 1 4/12/2013 Overview • overview of study designs • observational studies • clinical trials • basic biostatistics Classification of Study Designs observational • [case series, case reports] descriptive • ecological • cross-sectional • case-control • cohort analytical interventional • clinical trials 2 4/12/2013 Classification of Study Designs observational • [case series, case reports] non- • ecological longitudinal • cross-sectional • case-control • cohort longitudinal interventional • clinical trials Ecological Studies 3 4/12/2013 Ecological Studies • study of data at population/group level - no data on individuals • easily and opportunistically undertaken, often using routinely collected data • hypothesis-generating studies Ecological Study - Hypothetical Example 140 120 100 80 60 plots of Disease incidence individual countries 40 CANCER 20 20 40 60 80 100 120 140 Average smoking (cig/week) SMOKING 4 4/12/2013 Cross-Sectional Studies Cross-Sectional Studies • sample of population selected and information obtained at one point/period in time • large studies can take place over years, but each subject contributes data only once • that is, there is no follow-up of subjects 5 4/12/2013 Cross-Sectional Studies • data collected via: questionnaires ± examinations ± investigations • mostly descriptive outputs, especially prevalence eg, of CHD among Australians Example of Cross-Sectional Study 6 4/12/2013 Case Control Studies Case Control Studies • comparison of previous exposure status between: –subjects with outcome of interest (cases) –subjects without outcome of interest (controls) • controls are often matched with cases, 1:1 or n:1 • matching by confounders - eg: age, sex 7 4/12/2013 Case Control Studies time exposure outcome step 1: define and recruit cases; recruit controls by matching to cases (outcome ascertainment 1st) step 2: determine previous exposure among subjects Case Control Studies • explicit knowledge about temporal relationship between exposure and outcome • useful for studying rare outcomes • key output: odds ratio, approximation of relative risk of outcome conferred by exposure 8 4/12/2013 Hypothetical Example Controls: no Cases: Kafoop’s Kafoop’s Syndrome Syndrome No smoking 200 150 Smoking 100 150 OR = (200*150) / (100*150) = 2.0 Interpretation: smoking doubles likelihood of Kafoop’s Syndrome Kafoop’s Syndrome 9 4/12/2013 10 4/12/2013 Cohort Studies Cohort Studies • longitudinal, with follow-up of subjects • collect incidence data • comparison of outcomes between/among subgroups eg, not exposed vs exposed to risk factor • derive relative risks (recall examples from British Doctor’s Study) 11 4/12/2013 Prospective Cohort Study time exposure outcome Key: explicit knowledge about the temporal relationship between exposure and outcome. Retrospective Cohort Study time exposure outcome Key: explicit knowledge about the temporal relationship between exposure and outcome. 12 4/12/2013 Cohort Studies • explicit (often-detailed) knowledge about temporal relationship between exposure and outcome • can include multiple exposures and outcomes • research hypotheses can be addressed post hoc in established cohorts The Framingham Heart Study 13 4/12/2013 Framingham Risk Equation Clinical Trials 14 4/12/2013 “Clinically Proven” “Is it all a male conspiracy?” The Age 11 July 2002 15 4/12/2013 Clinical Trials • longitudinal studies designed to assess if an intervention (removal of exposure) changes the incidence of an outcome • most interventions are expected to decrease the incidence of the outcome • most involve a control group for comparison Clinical Trials intervention A assign intervention placebo / intervention B prospective follow-up to capture outcomes 16 4/12/2013 Clinical Trials • ‘gold standard’ for evidence of causality –active change of exposure status –tightly controlled study environment • provides most of the evidence for EBP 17 4/12/2013 Key Outcomes relative measures of intervention effect: • relative risks • hazard ratios absolute measures of intervention effect: • absolute risk/rate reduction • number needed to treat survival analysis Randomisation • random allocation of subjects into each arm of a clinical trial • objective: treatment groups identical in all aspects other than the intervention • rationale: reduce confounding 18 4/12/2013 Confounding exposure outcome confounder Confounding in Clinical Trials intervention outcome confounder (age/sex etc...) 19 4/12/2013 JAMA 2002; 288: 321-333. 20 4/12/2013 Basic Biostatistics Studies and Samples • studies are undertaken on samples of the population of interest (cf census) • studies are used to make inferences about the population of interest • biostatistics is concerned with the extent to which study (sample) results reflect the ‘truth’ 21 4/12/2013 p value • probability of the study result if it is assumed that the null hypothesis applies - truly no difference between the groups being compared • ie, probability that the study result was a chance finding • p value = conventional cut-off = 0.05 p < 0.05: statistically significant p ≥ 0.05: not statistically significant p = 0.02 p = 0.01 JAMA 2002; 288: 321-333. 22 4/12/2013 95% Confidence Interval • interval within which there is 95% confidence that the ‘true’ value lies • if the null value is excluded, result is stat significant • null value: value if the null hypothesis applies • null value: 1.0 for ratios (eg HR, RR, OR) and 0 for differences (eg absolute risk differences) JAMA 2002; 288: 321-333. 23 4/12/2013 WH RESEARCH TRAINING WORKSHOP 2013 Date: Thursdays ,12:30-1:30pm Venue: Auditorium Western Centre for Health Research & Education Sunshine Hospital Workshop Topic Presenters Date Research Ethics & Governance Dr Tam Nguyen 14-Feb-13 Introduction to Clinical Research Dr Harin Karunajeewa 28-Feb-13 Evaluating the literature A/Professor Kerrie Sanders 14-Mar-13 Writing a research proposal Dr Lizzie Skinner 28-Mar-13 Beginners statistics: Study Design Professor Danny Liew 11-Apr-13 Referencing and EndNote Dr Tam Nguyen & Lynn Higgins 24-Apr-13 Mixed Methods: Quantitative & Qualitative Professor Terrence McCann 9-May-13 Using Excel for research Dr Lizzie Skinner 23-May-13 Making sense of your results Professor Danny Liew 6-Jun-13 Getting your work published A/Professor Kerrie Sanders 20-Jun-13 Writing Abstract for Research Week/ Conferences Dr Debra Kerr 4-Jul-13 24 .
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