HAR202: Introduction to Quantitative Research Skills Dr Jenny Freeman [email protected] Page 1 Contents Course Outline: Introduction to Quantitative Research Skills 3 Timetable 5 LECTURE HANDOUTS 7 Introduction to study design 7 Data display and summary 18 Sampling with confidence 28 Estimation and hypothesis testing 36 Living with risk 43 Categorical data 49 Simple tests for continuous data handout 58 Correlation and Regression 69 Appendix 79 Introduction to SPSS for Windows 79 Displaying and tabulating data lecture handout 116 Useful websites*: 133 Glossary of Terms 135 Figure 1: Statistical methods for comparing two independent groups or samples 143 Figure 2: Statistical methods for differences or paired samples 144 Table 1: Statistical methods for two variables measured on the same sample of subjects 145 BMJ Papers 146 Sifting the evidence – what’s wrong with significance tests? 146 Users’ guide to detecting misleading claims in clinical research papers 155 Scope tutorials 160 The visual display of quantitative information 160 Describing and summarising data 165 The Normal Distribution 169 Hypothesis testing and estimation 173 Randomisation in clinical investigations 177 Basic tests for continuous Normally distributed data 181 Mann-Whitney U and Wilcoxon Signed Rank Sum tests 184 The analysis of categorical data 188 Fisher’s Exact test 192 Use of Statistical Tables 194 Exercises and solutions 197 Displaying and summarising data 197 Sampling with confidence 205 Estimation and hypothesis testing 210 Risk 216 Correlation and Regression 223 Page 2 Course Outline: Introduction to Quantitative Research Skills This module will introduce students to the basic concepts and techniques in quantitative research methods. Students will learn how to conduct a research project and use some simple statistical methods to analyse the resultant data. Aims 1. To introduce students to fundamental concepts and methods in quantitative research methods. 2. To give students an awareness of the processes involved in undertaking quantitative research. Learning Outcomes By the end of the unit, a student will be able to: 1. Classify and appropriately display and summarise different types of data. 2. Describe the properties of the Normal distribution. 3. Distinguish between a population and a sample, and understand what is meant by the term ‘standard error’. 4. Explain what a confidence interval is and interpret calculated confidence intervals as applied to means, proportions, differences in means, and differences in proportions. 5. Describe the process of setting and testing statistical hypothesis. 6. Distinguish between ‘statistical significance’ and ‘clinical significance’. 7. Undertake a simple piece of research and report the finding, both as a poster and written report Group Project Outline. Students and alcohol In groups you are to conduct a piece of quantitative research about students and alcohol. The groups will be allocated randomly by the lecturer. It is up to you to think of a topic; decide upon a research question to be investigated; formulate a hypothesis; design and conduct a study to test the hypothesis; analyse the results of the study; as a group present the results as a poster; write individual reports on the study findings. The individual reports should be in the style of the BMJ. Page 3 Assessment There will be two forms of assessment. 1. In their project groups, the students will be expected to produce and present a poster of the results of their research project (20%). The presentation will be of 10 mins duration. 2. Individually, each student will be expected to produce a project report of between 1,000 to 1,500 words, in the style of a quantitative paper in the BMJ (.e. abstract, introduction, methods, results, discussion and conclusions and references) (80%). Page 4 Timetable Date Lecture title 14th Feb Introduction to Module At the end of this session you should: · Know about the different study designs used in quantitative research · Be able to distinguish between the different types and know when they are appropriate · Be able to distinguish between the strength of evidence provided by the different study designs 21th Feb Displaying data At the end of this session you should: · Know about the different types of quantitative data and be able to distinguish between them · Be able to display data appropriately using a variety of charts · Calculate basic summary measures · Be aware of the elementary properties of the Normal distribution 28nd Feb Sampling At the end of this session you should: · Be able to distinguish between a population ad a sample · Know about different methods of sampling · Be able to calculate and understand what is meant by the term standard error(se) and be able to distinguish this from the standard deviation (SD) · Understand what is meant by the term confidence interval 7st March Hypothesis testing At the end of this session students should: · Know about the process of setting and testing statistical hypotheses · Be able to explain o Null hypothesis o P-value o Type I error o Type II error o Power · Demonstrate awareness that the p-value does not give the probability of the null hypothesis being true and that p>0.05 does not mean that we accept the null hypothesis · Distinguish between ‘statistical significance’ and ‘clinical significance’ Page 5 14th March Risk At the end of this session students should: · Know about different measures of risk · Be able to explain o Risk o Relative risk o Odds and Odds ratio o Absolute risk reduction/excess o Number needed to treat · Be familiar with concept of risk ladders 10th April SPSS 1 17th April Analysis of categorical data At the end of this session students should: · Be able to recognise categorical data · Be able to compare o a single proportion to some pre-specified value o two proportions · Know how to analyse data expressed in frequency tables o 2x2 tables 24th April Analysis of continuous data At the end of this session students should: · Know the difference between parametric and non-parametic tests · Be aware that data are not non-parametric, it is the test that is · Be able to carry out simple statistical tests o Paired and unpaired t-test o Sign test o Wilcoxon signed rank test o Mann-Whitney U test 1st May Regression and correlation At the end of this session students should: · Display bivariate qualitative data graphically or in table form · Construct and interpret scatterplots for bivariate quantitative data · Recognise the appropriate uses of correlation and regression · Interpret correlation coefficients and regression equations 8th May SPSS 2 15th May How to mislead with statistics 22nd May Poster Presentation Page 6 LECTURE HANDOUTS Introduction to study design At the end of session, should know about: Study Design • Types of study design commonly used in quantitative research Dr Jenny Freeman Lecturer in Medical Statistics At the end of session, should be able to: • Distinguish between different types of quantitative study design and know when they are appropriate • Distinguish between the strength of evidence provided by different study designs Quantitative Research Process Main aim of design • Have an idea •Most studies try to relate an input to an • Formulate a hypothesis output • Design study –Do mobile phones cause brain cancer? • Collect data –Do statinsreduce heart disease? •They try to establish the relationship and • Analyse data to quantify it Drawn conclusions • •A good design will have maximum • Disseminate results precision, minimum bias and with fewest resources Bias present, low precision Bias present, high precision x x x x x x x x x x x Categories of Research Design x x x x x xxx x x x x x x xxxxx xxxxx x xx Research study design can be classified in several ways, for example: No bias present, low precision No bias present, high precision • Observational or experimental • Prospective or retrospective x x x x x x x x x x x xxx x x x x xxxxx x x x xxxxx • Longitudinal or cross-sectional x x x x x xx Page 7 Observational or experimental? Observational or experimental? Observational Experimental • Researcher collects information on the • Researcher deliberately influences events attributes or measurements of interest but does not influence events. Studies of this and investigates the effects of the type include surveys, case-control studies intervention. Studies of this type include and cohort studies randomised controlled trials and many laboratory and animal studies • Observational studies may also be comparative, but they are most commonly • Generally, stronger inferences can be made descriptive from experimental studies • Experimental studies are usually carried out to make comparisons between groups Prospective or retrospective? Prospective or retrospective? Prospective Prospective •Historical controls • Data are collected forwards in time from • Egcompare survival of patients who have had heart transplant with similar patients before heart transplantation the start of the study became available • Examples include experiments •Before-and-after studies • EgMills et al evaluated whether a Government education (including randomised controlled trials) campaign had increased public knowledge of AIDS- questionnaires sent to a random sample of population and some observational studies (eg before and after campaign. cohort study) •Quasi-experimental studies • To compare groups, some of whom got an intervention and others not-perhaps for administrative convenience Prospective or retrospective? Cross-sectional Survey Retrospective