View
35
Download
0
Category
Tags:
Preview:
DESCRIPTION
NTR 629 - Week 2. Research Design Classification. How Study Designs Differ. Number of observations made Directionality of exposure Data collection methods Timing of data collection Unit of observation Availability of subjects. Study Design Approaches. Experimental Approaches. - PowerPoint PPT Presentation
Citation preview
Company
LOGO
Research DesignClassification
NTR 629 - Week 2
1
2
How Study Designs Differ
Number of observations made Directionality of exposure Data collection methods Timing of data collection Unit of observation Availability of subjects
Experimental Approacheso Manipulation (exposure of
interest controlled by the investigator)
o Hypothesis testing o Examines cause-effecto Quantitative and analytic
Experimental Design Most rigorous design.
Randomization of study subjects/units
Quasi-experimental Design Less rigorous, because no
randomization of study subjects/units
Observational Approaches No manipulation No randomization of study
subjects/units Less rigorous than
experimental designs Analytic or descriptive
Analytic studies E.g., many ecologic
studies, case-control studies, cohort studies
Descriptive studies: E.g. cross-sectional
surveys
Study Design Approaches
Analytical Experimental Quasi Experimental Pre-Experimental Cohort studies Case Control (or Single
Subject) Historiography Analytical Survey Content Analysis Causal-Comparative
Descriptive Case Study Case Series Developmental Correlational Descriptive Survey Field/Ethnographic
Classification Based on Purpose
Analytical Test hypothesis Allows detection of causal
associations Numerical data –
quantitative.
Descriptive No true hypothesis Establishes a relationship Describes state of nature
at point in time No control of variables Recording of
observations Primarily to totally
qualitative
Design Characteristics
Company
LOGO
Analytical Designs (Part 1):Experimental Designs
True Experimental Design
Pretest post-test control group design TWO (or more) groups:
Random/control group O1 O2 Random/experimental group O1 X O2
Caution with within-session variation between treatments A and B… control conditions. Pretest important if need to check equivalence of groups.
Key for Study Design Symbols: O1 = observation 1 (measurement of dependent variable) X = manipulated variable; independent variable O2 = observation 2 (measurement of same dependent variable as O1)
True Experimental Design
Pretest post-test control group design THREE groups:
Random/control group O1 O2 Random/experimental group A O1 XA O2 Random/experimental group B O1 XB O2
Caution with within-session variation between treatments A and B… control conditions. Pretest important if need to check equivalence of groups.
True Experimental Design
Post-test only control group design TWO (or more) groups:
Random/control group O2 Random/experimental group X O2
No pretest? Assume equivalence with randomization. No interaction effect with pretesting.
True Experimental Design
Solomon four group design FOUR groups:
Random/experimental group O1 X O2 Random/control group 1 O1 O2 Random/control group 2 X O2 Random/control group 3 O2
Important if taking pretest influences post-test.
Quasi Experimental Design
Nonequivalent control group design TWO groups:
Experimental group O1 X O2 Control group O1 O2
Uses intact groups (e.g., class); no randomization
Quasi Experimental Design
Static group design TWO groups:
Experimental group X O2 Control group O2
Uses intact groups (e.g., class); no randomization
Quasi Experimental Design Counterbalanced design
FOUR (or more) groups (A, B, C, D) and FOUR (or more) treatment variations (1, 2, 3, 4), with exposure at different times during study:
ReplicationTreatment Variations
XA XB XC XD1 A B C D2 B D A C3 C A D B4 D C B A
Uses intact groups (e.g., class); no randomization
Quasi Experimental Design
Single subject design ONE subject:
Experimental subject base-O1 X withdraw-X O2
“Behavioral”, natural setting, little generalizability
Quasi Experimental Design
One group time series design ONE group:
Experimental groupO1 O2 O3 O4 X O5 O6 O7 O8
Determine if effect of X, and if X is short-term effect.
Quasi Experimental Design
Control group time series design TWO groups:
Experimental group O1 O2 O3 O4 X O5 O6 O7 O8
Control group O1 O2 O3 O4 O5 O6 O7 O8
Helps control selection-maturation effects.
Quasi Experimental Design
Control group time series design FIVE (or more) groups:
Experimental group A O1 X O2 Experimental group B O1 X O2 Experimental group C O1 X O2 Experimental group D O1 X O2 Experimental group E O1 X O2
Helps control maturation, pretest, regression, history
Factorial Design
2x2 factorial design To examine interaction effects of two or more
independent variables (X) and test several H0 simultaneously.
Teaching method (X1) Length of period (X2)50 minutes 30 minutes
Discussion O1 O2
Lecture O3 O4
Factorial Design There are many variations of factorial
designs. The variables can have multiple levels. E.g.,: 2x3 design
two X (X = manipulation): one with two levels, one with three levels
3x3 design Three X, each with three levels
2x2x2 design Three independent variables, each varied two
ways
Advantages Experimental Design
Comparing outcomes in treated group compared to an equivalent control group
Participants in both groups are enrolled (random assignment into group), treated, and followed over the same time period
Single or double-blinded. Used to test efficacy of
preventive (prophylactic) or therapeutic (curative) measures
Multicenter trials--results from several researchers pooled.
Limitations Artificial setting Limited scope of potential
impact Adherence to protocol is
difficult to enforce Possible ethical dilemmas
Controlled Clinical Trials
Schematic Diagram of a Clinical Trial
SAMPLE
Randomization to groups
Intervention group Control group
Measure outcome Measure outcome
Lost to follow-up
Nonparticipants
Clinical Trial Crossover Designs
Any change of treatment for a patient in a clinical trial involving a switch of study treatments.
Planned crossovers Protocol is developed in
advance, and the patient may serve as his or her own control.
Unplanned crossovers Exist for various reasons,
such as patient’s request to change treatment.
Members of both groups receive both treatment regimens
Group 1 receives treatment A then treatment B
Group 2 receives treatment B then treatment A
Treatment A
Treatment B
Advantages Represents the only way to
estimate directly the impact of change in behavior or modifiable exposure on the incidence of disease.
Community intervention trials determine the potential benefit of new policies and programs.
Community refers to a defined unit, e.g., a county, state, or school district.
Limitations Inferior to clinical trials with
respect to ability to control entrance into study, delivery of the intervention, and monitoring of outcomes.
Fewer study units are capable of being randomized, which affects comparability.
Affected by population dynamics, secular trends, and nonintervention influences
Community Trials
Community Trials - Steps Community trials start by:
Determining eligible communities and their willingness to participate
Collect baseline measures of the problem to be addressed in the communities, e.g., disease rates, knowledge, attitudes, and practices
Communities are randomized (intervention and control)
Followed over time Outcomes of interest are measured
Recommended