Planning a Study

1
Planning a Study

• Deciding what
• and how to measure

2
Vocabulary

• Measuring What?
• Units
• Experimental Units
• Subjects
• Participants

• Various Variables
• Explanatory (independent) variable
• Response (dependent) variable
• Confounding variable
• Lurking variable

3
Experiment

• Subjecting the sample to a controlled treatment
  where one variable is altered.
• The objects on which the treatment is imposed on
  are called experimental units (human subjects).
• Explanatory variables are called factors and
  specific values of the explanatory variable are
  levels.

4
Designing a Good Experiment

• Randomization--randomly assign subjects to
  treatment and control groups
• Control
• Replication--consistency
• Differences in the response variable between
  groups, if enough to rule out natural chance
  variability, can then be attributed to the
  manipulation of the explanatory variable. This
  will allow determination of cause and effect.

5
Randomization--Crucial

• Researchers do experiments to reduce the
  likelihood that the results will be affected by
  confounding variables and other sources of bias.
• Randomize Type of Treatment
• Randomize Order of Treatment

6
Control Groups

• Control group--receives standard treatment OR
• Placebo (sham) group--receives no treatment
• Single-Blind
• Double-Blind
• These control for UNKNOWN variability

7
Designing Control

• Block Design--divide units into homogeneous
  groups (called blocks) and each treatment is
  randomly assigned to one or more units in each
  block.

• Matched-Pair Design--assigned either two matched
  individuals (identical twins) OR the same
  individual (repeated measure) to receive the two
  treatments

This controls for KNOWN variability.
8
Quitting Smoking w/Nicotine Patches

• Recruited 240 smokers (volunteers) at Mayo Clinic
  from 3 large cities
• Randomly assigned 22-mg nicotine
• patch or placebo patch for 8 weeks.
• All attended counseling before, during, and
  after.
• Double-blind (neither volunteers nor nurses
  taking measurements knew type of patch)
• After 8-wk (1 yr), 46 (27.5) of nicotine patch
  group quit smoking and 20 (14.2) of placebo
  group quit.

9
Observational Study

• Observing the behaviors of a sample from a
  population.
• The observer does not impose active treatments on
  units/subjects.
• Or using previously collected data to do
  statistical analysis.

10
Census--Observational Study

• The systematical collection of data on the entire
  population.
• When the population is large, it will become time
  consuming and expensive.

11
Sample Survey--Observational Study

• A portion of the population is asked a question
  and the study is done based on their voluntary
  answers.

12
03-08-93 Newsweek announced A Really Bad Hair
Day Researchers link baldness and heart
attacks. The article reported that men with
typical male pattern baldnessare anywhere from
30 to 300 percent more likely to suffer a heart
attack than men with little or no hair loss at
all. The report was based on an observational
study conducted by researchers at Boston Univ.
School of Medicine. They compared 665 men who had
been admitted to the hospital with their 1st
heart attack to 772 men in the same age group
(21- to 54-years old) who had been admitted to
the same hospital for other reasons.
13
Case Control Studies--Observational Study

• Cases who have a specific attribute/condition
  are compared to Controls who dont.
• Efficiency
• Reduces potential confounding variables
• Retrospective vs. Prospective

14
Characteristics of a well-designed and
well-conducted survey

• Trained interviewers must be consistent with
  asking neutral, non-leading questions.
• An unbiased sampling should represent the
  population of interest.

15
Populations?Random Selections?Samples
16
Sampling Methods

• Simple Random Sample (SRS)
• Stratified Random Sampling
• Cluster Sampling
• Systematic Sampling
• Multi-Stage Sampling

• Random Digit Dialing
• Self-Selected Sample
• Convenience Sample
• Quickie Polls

17
Simple Random Sampling

• From the entire population every possible
  grouping of specified size has same chance of
  being selected.

18
Stratified RS vs Cluster S

• 1st divide population into groups (strata), then
  take a Simple Random Sample from each strata

• 1st divide population into groups (cluster), then
  randomly select some clusters and sample everyone
  in that cluster

19
Systematic Sampling Random Digit Dialing

• From a list, divide into consecutive segments
  (every 50 names), randomly choose starting point
  (21st entry), then sample at that same point in
  each segment (21, 71, 121, 171, )

• Sample that approximates a SRS of all households
  in US that have telephones with a specific
  exchange
• (210-695-????)

20
Multi-Stage Sampling

• survey designers might stratify population by
  region of country, then stratify by urban,
  suburban, or rural, then choose a random sample
  of communities within those strata. They would
  continue to divide communities into city blocks
  (fixed areas) as clusters, and sample from the
  selected clusters.

21
Self-Selected Sample--radio station
call-inConvenience Sample--surveying folks in a
mall who appear willing to talk to youQuickie
Polls--hastily designed, poorly pre-tested, one
night survey sample for evening news show
22
Sources of bias in surveys

• If a selection process consistently obtains
  values too high or too low, then BIAS exists.
• ?Selection Bias
• ?Non-response Bias
• ?Response Bias

23
Survey Questions

• Unnecessary complexity to question
• Misleading question
• Ordering of questions
• Ensuring confidentiality
• Anonymous survey

24
Gathering Data

• Experimental Design

• Observational Study