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An overview of the steps involved in designing experiments and collecting samples for research. Topics include randomization of subjects, defining the population, use of placebos, measurement, cautions about experimentation, and the science of sampling. It also covers different types of samples, sampling bias, and the development of scientific sampling.
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Module 3 – Producing Data^1
François Nielsen
University of North Carolina Chapel Hill
Fall 2009
(^1) Adapted in part from slides for course taught by John Fox (McMaster
University) and Robert Andersen (University of Toronto)
Main Sections
… (^) Introduction … (^) Design of Experiments … (^) Sampling Design … (^) Toward Statistical Inference
… (^) Available data are data that were produced in the past for some other purposes but that may help answer a present question. … (^) Examples: … (^) Historical records of the numbers of young men and women graduating from high school (kept since 1870) reveal that until about the 1970s, women in the U.S. graduated at a higher rate than men. … (^) The National Center for Health Statistics keeps records on the causes of death by age groups and gender. … (^) Principal causes of death of 20–24 year old are accidents, homicide, and suicide; overall death rate is three times higher for men. … (^) A Belgian demographer uses parish records of the 1600s to study trends in age at marriage, fertility and infant mortality.
Sample Surveys
… (^) In a sample survey a small subset of a larger population is systematically selected to provide information on the larger population. … (^) The General Social Survey has sampled 1,500–3,000 adults in the U.S. every other year since 1972. … (^) Opinion polls sample about 1,000 likely voters. … (^) Employment surveys such as the Current Population Survey (CPS) in the U.S. sample about 60,000 households. (Why so many?)
Problem of Observational Studies
… (^) Study of 1364 infants followed up to grade 6 found that children who had been in daycare from infancy to age 4. found that time spent in daycare was associated with: … (^) getting along less well with others … (^) greater assertiveness … (^) more disobedience … (^) greater aggressiveness … (^) But: Effect of daycare is confounded with other characteristics of families using daycare. (Which?)
Terminology of Experimental Designs
… (^) The individuals on which the experiment is done are the experimental units. … (^) When the units are humans, they are called subjects or participants. … (^) A specific experimental condition applied to the units is called a treatment. … (^) The explanatory variables in an experiment are often called factors. … (^) In multi-factorial experiments, each treatment is formed by combining a specific level (value) of each of the factors.
Natural Experiments
… (^) In a natural experiment a change in the environment occurs naturally. … (^) Measures of the response variable are taken before and after the event. … (^) Occasions are rare, but can be instructive. … (^) Examples: … (^) Homicide rates of U.S. states are compared before and after passage of gun control legislation. … (^) Rates of birth defects are compared before and after the marketing (at different times) of Thalidomide in British counties. … (^) Problem: no control group to compare to.
… (^) In a field experiment a change in environment is introduced in a natural setting. … (^) An example is the gastric freezing experiment in which patients ingesting a deflated balloon later filled with refrigerated liquid experienced relief from pain. … (^) Problems: … (^) No control group to compare to – we don’t know what would happen if the intervention had not taken place. … (^) Also sensitive to placebo effect: … (^) Spontaneous recovery from medical condition over time. … (^) Benefit from any treatment. … (^) Uncontrolled experiments in medicine and social sciences (as opposed to physical sciences) often biased by subject selection and placebo effects. … (^) Later controlled experiment showed gastric freezing was no better than placebo.
Random Assignment
… (^) Most experiments have multiple groups. … (^) When all experimental units are allocated at random among all treatments, the design is called completely randomized. … (^) Subjects are placed into the experimental or control groups using a true random process : … (^) Each case has an equal chance of ending up in any group – e.g., subjects’ names are put into a hat and pulled out randomly. … (^) It is a purely a mechanical process – the researcher has no control over placement. … (^) Random assignment to groups may be done manually with a table of random digits, or with software (next slide).
Example of Random Group Assignment
. * in Stata . * want 16 groups of 6 subjects . clear . set obs 96 . generate lab=_n . generate random=runiform() . list in 1/
+----------------+
| lab random |
|---|
| 5 .684176 |
|---|
+----------------+
| lab random |
|---|
| 8 .0610638 |
|---|
Overall Structure of a Classical Experimental Design
Random Allocation
Compare Differences in DV
Experimental Group Treatment
Control Group No treatment
Randomi- zation Pretest (^) Treatment Posttest
E.g., Impact of TV violence on attitudes
E.g., New teaching method and grades
… (^) We want to improve grades in methods courses
Internal Validity: Was the treatment the true cause of a change in the dependent variable?
