Week_5_Experimentation & Measurement and scaling Flashcards
What is causality?
For instance: an association between attitude and behavior is evidence of a causal relationship.
Means
1) that a change in one variable will produce a change in another.
2) If two variables are causally linked they should be associated.
3) If association provides evidence of causation, then lack of association suggest an absence of causation.
Before making causal inference, you must make sure 3 factors:
- Concomitant variation - evidence that a strong association exists between an action and an observed outcome.
- The time order of occurrence - causing event must occur before or simultaneously with the effect.
- absence of other possible causal factors - the factor or variable being investigated should be the only possible causal explanation.
Even 3 factors are satisfied, still can not determine the causality exists
What is difference between independent variables and dependent variables.
IV are variables or alternatives that are manipulated; DV are the variables which measure the effect of the independent variables on the test units.
Relationship with test unit and variables.
test unit are individuals or entities response to the independent variables.
What is extraneous variables?
All variables other than independent variables that affect the response of the test units.
Internal validity definition
A experiment that determine whether the independent variable cause the effect of dependent variables
Control of extraneous variables is a necessary condition for establishing internal validity.
External validity definition
A determination of whether the cause-and- effect relationships found in the experiment can be generalized.
What are categories in extraneous variables
History - specific events that are external to the experiment but occur at the same time as the experiment
Maturation - refers to changes in the test units themselves that occur with the passage of time.
Testing effects - caused by experimentation, including main testing effect and interactive testing effect
Instrumentation - changes in the measuring instrument.
Statistical regression - occur when test units with extreme scores move closer to the average score during the course of the experiment.
Selection bias - An extraneous variable attributable to the improper assignment of test units to treatment conditions.
Mortality - loss of test units while the experiment is in progress.(人死了,影响结果)
Treatment Effect (TE)
(O2 - O1) - (O3 - O4), make sure the result is effected only by TE
What do these symbols represent: X, O, R
X = independent variable, treatment, or event, the effects of which are to be determined O = dependent variables on test units or group units R = the random assignment of test units or groups to separate treatments
Ways to control extraneous variables
Randomization - randomly assigning test units to experimental groups.
Matching - matching test units on a set of key back- ground variables before assigning them to the treatment conditions.
Statistical control - measuring the extraneous variables and adjusting for their effects through statistical methods.
Design control - involves using specific experimental designs
Classification of experimental design
Pre-experimental design - one shot case study, not really great.
True experimental - two group including control group and random group.
Quasi-experimental design - Designs that apply part of the procedures of true experimentation but lack full experimental control.
Statistical design - allow for the statistical control and analysis of external variables.
One-shot case study
X, O1 - Single group of test units is exposed to treatment X; A single measurement on the dependent variable is taken (O1). no random assignment of test units (no R). more appropriate for exploratory.
One-group pretest-posttest design
O1 X O2
Static group design
EG: X 01
CG: 02
True Experimental Designs: Pretest-Posttest Control Group Design
EG: R 01 X 02
CG: R 03 04
Quasi-experimental design - time series design
Two kinds: single time and multiple time
01 02 03 04 05 X 06 07 08 09 010
EG : 01 02 03 04 05 X 06 07 08 09 010
CG:01 02 03 04 05 06 07 08 09 010
When is Randomized Block Design from statistical design useful?
Only one major external variable
When is Latin Square Design useful?
When two non-interacting external variables are allowed as well as independent variable are manipulated
When is factorial design useful?
When two or more independent variables.
Differences between Laboratory experiment an field experiments
Laboratory experiment is easier to control than field experiment does. But field experiment is better to get good result