Review. Chapter 5. Common Language. Ch 3: samples. Ch 4: real world sample surveys. Experiments, Good and Bad

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1 Review Ch 3: samples Sampling terminology Proportions Margin of error Ch 4: real world sample surveys Questions to ask about a study Errors in sample surveys Concerns about survey questions Probability sampling plans Chapter 5 Experiments, Good and Bad Chapter 5 6 Common Language Response variable what is measured as the outcome or result of a study Explanatory variable what we think explains or causes changes in the response variable often determines how subjects are split into groups Subjects the individuals that are participating in a study Treatments specific experimental conditions (related to the explanatory variable) applied to the subjects 1

2 Case Study Quitting Smoking with Nicotine Patches (JAMA, Feb. 23, 1994, pp ) Variables: Explanatory: Treatment assignment Response: Cessation of smoking (yes/no) Treatments Nicotine patch Control patch Random assignment of treatments Randomized Experiment versus Observational Study Both typically have the goal of detecting a relationship between the explanatory and response variables. Experiment create differences in the explanatory variable and examine any resulting changes in the response variable Observational Study observe differences in the explanatory variable and notice any related differences in the response variable Why Not Always Use a Randomized Experiment? Sometimes it is unethical or impossible to assign people to receive a specific treatment. Certain explanatory variables, such as handedness or gender, are inherent traits and cannot be randomly assigned. 2

3 Experiments: Basic Principles Randomization to balance out extraneous variables across treatments Placebo to control for the power of suggestion Control group to understand changes not related to the treatments Confounding (Lurking) Variables The problem: in addition to the explanatory variable of interest, there may be other variables that make the groups being studied different from each other the impact of these variables cannot be separated from the impact of the explanatory variable on the response Confounding (Lurking) Variables The solution: Experiment: randomize experimental units to receive different treatments (possible confounding variables should even out across groups) Observational Study: measure potential confounding variables and determine if they have an impact on the response (may then adjust for these variables in the statistical analysis) 3

4 Statistical Significance If an experiment or observational study finds a difference in two (or more) groups, is this difference really important? If the observed difference is larger than what would be expected just by chance, then it is labeled statistically significant. Rather than relying solely on the label of statistical significance, also look at the actual results to determine if they are practically important. Chapter 6 Experiments in the Real World Chapter 6 19 Experiments: Some Techniques Double-blinding to control experimenter/respondent bias Pairing or blocking to reduce a source of variability in responses the same or similar subjects receive each treatment different from a completely randomized design, where all subjects are allocated at random among all treatments 4

5 Experiments: Difficulties and Disasters Extraneous variables Confounding variables (in chapter 5) Interacting variables Hawthorne, placebo, and experimenter effects Refusals, nonadherers, dropouts Extending the results (generalizing) Interacting Variables The problem: effect of explanatory variable on response variable may vary over levels of other variables. The solution: measure and study potential interacting variables. does the relationship between explanatory and response variables change for different levels of these interacting variables? if so, report results for different groups defined by the levels of the interacting variables. Interacting Variables: Case Study Quitting Smoking with Nicotine Patches (JAMA, Feb. 23, 1994, pp ) smoker at home found this to be an interacting variable: Percent quitting Nicotine Placebo Smoker at home 31% 20% No smoker at home 58% 20% other variables: age, weight, depression no interactions found 5

6 Hawthorne, Placebo, and Experimenter Effects The problem: people may respond differently when they know they are part of an experiment. The solution: use placebos, control groups, and doubleblind studies when possible. Extending the Results ( ecological validity ) The problem: lack of generalizability due to: unrealistic treatments unnatural settings sample that is not representative of population The solution: Researchers should use natural settings with a properly chosen sample. Chapter 7 Data Ethics Chapter

7 Ethical Considerations in Statistical Studies: 1. Ethical treatment of human and animal participants 2. Assurance of data quality 3. Appropriate statistical analyses 4. Fair reporting of results National Research Act (1974) Tuskegee led to the National Research Act that requires Institutional Review Boards (IRBs) at institutions receiving federal grants. Informed Consent Experiments with human participants require that researchers obtain informed consent of participants. Participants told what research is about, and given opportunity to make choice whether to participate. Participants can t be told everything in advance. Experiments with control and blinding: use of multiple groups is explained and participants told they will be randomly assigned to a group but will not know which until conclusion of experiment. 7

8 Clinical Trials Experiments that study the effectiveness of medical treatments on actual patients Need comparative experiments to see true effects of new treatments Balance future benefits against present risks Interests of the subject must always prevail over the interests of science and society Clinical Trials Controversies Belief that the treatment is effective to justify exposing subjects to it; doubt that the treatment is effective to justify withholding it from other subjects When is the treatment effective enough to stop the study and assign the treatment to the placebo or control groups also? When is the treatment harmful enough to stop the study and discontinue use of the treatment? Who can give consent? 8