Unit 4 Gathering Data LESSON 4-3 – OBSERVATIONAL STUDIES HOW DO WE CONDUCT OBSERVATIONAL STUDIES?

Learning Objective 0: Why Sample?  We need to select a sample of individuals when we conduct an observational study. Sampling is necessary because it would be expensive, time consuming, and almost impossible to sample an entire population.  To make sure our sample is representative of the population, we need to select a good sample for our observational study.

Learning Objective 1: Random Sampling Designs METHOD 1: SIMPLE RANDOM SAMPLING (covered in 4-2) PROCESS/STEPS  Develop sampling frame (list entire population ‘N’ people)  Use random selection method  Carry out selections to get ‘n’ people for sample

Learning Objective 1: Random Sampling Designs METHOD 1: SIMPLE RANDOM SAMPLING (covered in 4-2) ADVANTAGE(S)  Everyone in the population has an equal chance of being selected  It’s very random; possible to get a good representative sample DISADVANTAGE(S)  You need to know everyone in your entire population and construct a list of all of them  It’s very random; possible to get a poor representative sample

Learning Objective 1: Random Sampling Designs METHOD 1: SIMPLE RANDOM SAMPLING (covered in 4-2) EXAMPLE: We need to select a sample of 200 students at Boulder Creek to give them a school satisfaction survey (1343 male, 1221 female) 715 freshmen, 658 sophomores, 610 juniors, 581 seniors, 118 teachers How do we do it with simple random sampling? (discuss)  List of all students, number them, select 200 random numbers OR  Generate random 6-digit numbers and match them up with 200 students.

Learning Objective 1: Random Sampling Designs METHOD 2: SYSTEMATIC SAMPLING PROCESS/STEPS  Create a list of every member in the population of interest  Randomly select a starting point for the sample and continue selecting and building your sample with every ‘nth’ person

Learning Objective 1: Random Sampling Designs METHOD 2: SYSTEMATIC SAMPLING ADVANTAGE(S)  Easier to get the sample without generating and matching up random numbers with members of the population DISADVANTAGE(S)  Still need a sampling frame

Learning Objective 1: Random Sampling Designs METHOD 2: SYSTEMATIC SAMPLING EXAMPLE: We need to select a sample of 200 students at Boulder Creek to give them a school satisfaction survey (1343 male, 1221 female) 715 freshmen, 658 sophomores, 610 juniors, 581 seniors, 118 teachers How do we do it with systematic sampling (discuss)  List of all students, number them, select a random ‘nth’ number to count by and get 200 samples.  Can we just ask every 15 th student to walk through each gate to take the survey?

Learning Objective 1: Random Sampling Designs METHOD 3: CLUSTER SAMPLING PROCESS/STEPS  Divide the population into large number of clusters (often geographically or by location)  Every member of the population belongs to one group/cluster only  Randomly select a sample of clusters  Survey/sample all the individuals in those selected clusters

Learning Objective 1: Random Sampling Designs METHOD 3: CLUSTER SAMPLING ADVANTAGE(S)  Easy to establish groupings/clusters (they exist already)  No sampling frame needed, just a list of people/contact info within the clusters selected DISADVANTAGE(S)  Individuals within a certain cluster may have similar opinions, so...  …Bias in some clusters might keep sample from being as representative as other populations  Difficult to know how many samples will be available, as clusters contain different amounts of members

Learning Objective 1: Random Sampling Designs METHOD 3: CLUSTER SAMPLING EXAMPLE: We need to select a sample of 200 students at Boulder Creek to give them a school satisfaction survey (1343 male, 1221 female) 715 freshmen, 658 sophomores, 610 juniors, 581 seniors, 118 teachers How do we do it with cluster sampling? (discuss)  Group students by classroom, building, cafeteria table, area of parking lot, etc. Randomly select 7 classrooms and survey everyone in that class.  What is a potential problem with this sampling plan?

Learning Objective 1: Random Sampling Designs METHOD 4: STRATIFIED SAMPLING PROCESS/STEPS  Divide the population into separate groups, called strata (by characteristics generally, not location)  Select a random sample from each (and every) strata

Learning Objective 1: Random Sampling Designs METHOD 4: STRATIFIED SAMPLING ADVANTAGE(S)  Will usually give you the most diverse and well representative sample (limits bias)  You know the size of each strata, so you can adjust how many samples you get from each DISADVANTAGE(S)  Must be able to sort everyone into a single strata  Must have a sampling frame still within each strata

Learning Objective 1: Random Sampling Designs EXAMPLE: We need to select a sample of 200 students at Boulder Creek to give them a school satisfaction survey (1343 male, 1221 female) 715 freshmen, 658 sophomores, 610 juniors, 581 seniors, 118 teachers How do we do it with stratified sampling? (discuss)  List of students who are taking certain classes, by grade level, by gender, etc. Sample a set number from each.  Is 50 from each grade level sufficient and balanced?

Learning Objective 2: Types of Observational Studies  A well-designed, informative observational study can yield useful information when experiments are not possible, due to being expensive, time consuming, and/or harmful to people (physically or mentally).  Remember! Causation can never be definitively established with an observational study, but well- designed studies can provide supporting evidence for the researcher’s beliefs. Now we will look at the 3 types of observational studies…

Learning Objective 2: Types of Observational Studies  Types of Observational Studies:  Sample Survey: attempts to take a cross section of a population at the current time  Example: “How often do you consume honey?”  Retrospective Study: examines past data to make connections  Example: “How frequently did you eat honey as a child?” and “Do you struggle with allergies?”  Prospective Study: follows selected subjects into the future to evaluate connections between two or more variables  Example: We (a research team) will take 100 individuals and evaluate how their allergies change each year based on a 20 question lifestyle checklist. 10 years later we will evaluate the results.

Learning Objective 2: Types of Observational Studies RETROSPECTIVE STUDIES  A retrospective study looks backwards (it’s retro) and examines exposures to suspected risk or protection factors in relation to an outcome that is established at the start of the study.  Most sources of error due to confounding and bias are more common in retrospective studies than in prospective  A case-control study is they most typical type of retrospective study in which subjects who have a response outcome of interest (the cases) and subjects who have the other response outcome (the controls) are compared on an explanatory variable studies.

Learning Objective 2: Types of Observational Studies Example of a Retrospective, case-control study: Response outcome of interest: lung cancer  The cases have lung cancer  The controls did not have lung cancer  The two groups were compared on the explanatory variable: smoker/nonsmoker Lung Cancer? CasesControls Smoker Non-Smoker TOTAL 709 Probability Of Being a Smoker

Learning Objective 2: Types of Observational Studies PROSPECTIVE STUDIES  A prospective study watches for outcomes, such as the development of a disease, during the study period and relates this to other factors such as suspected risk or protection factor(s).  The study usually involves taking a cohort of subjects and watching them over a long period.  The outcome of interest should be common; otherwise, the number of outcomes observed will be too small to be statistically meaningful (indistinguishable from those that may have arisen by chance).  All efforts should be made to avoid sources of bias such as the loss of individuals to follow up during the study.  A cohort study is the most common type of prospective study.

Learning Objective 2: Types of Observational Studies PROSPECTIVE STUDY EXAMPLE The Framingham Heart Study was a famous prospective, cohort study conducted in Massachusetts, as an ambitious project in health research in Starting with just 5,209 participants (all volunteers), that study has revolutionized the treatment of heart disease by linking it with hypertension and high cholesterol levels. As it happens, in 1971 a further 5,100 participants - children of the original cohort and their spouses – were recruited to carry this study into a second generation. The study is no longer just focused on heart disease, it now includes cancer, dementia, arthritis, osteoporosis and hearing and eye disorders. A staggering 1,000 scientific papers have been published from discoveries made through the study of this cohort. Showing strong support, 3,900 grandchildren of the Framingham Heart Study's original participants - enrolled in the Framingham “Third Generation Study” in Key goals in this third-generation study are to identify new risk factors for heart, lung, and blood diseases, identify genes that contribute to good health and to the development of heart, lung, and blood disease, and to develop new imaging tests that can detect very early stages of coronary atherosclerosis in otherwise healthy adults.

Learning Objective 2: Types of Observational Studies PROSPECTIVE  outcome is measured after exposure  may uncover unanticipated associations with outcome  best for common outcomes  expensive  requires large numbers  takes a long time to complete  prone to attrition bias  prone to the bias of change in methods over time RETROSPECTIVE  outcome is measured before exposure  controls are selected on the basis of not having the outcome  good for rare outcomes  relatively inexpensive  smaller numbers required  quicker to complete  prone to selection bias  prone to recall/retrospective bias