Ch.6 Independent Groups Design Flashcards
Internal validity
an experiment has internal validity when we can state confidently that the independent variable caused differences between groups on the dependent variable (a causal inference)
Three conditions for casual inference
covariation, time-order relationship, elimination of plausible alternative causes
Covariation
relationship between IV and DV
Time-order relationship
presumed cause precedes the effect
Elimination of plausible alternative causes
use control techniques to eliminate other explanations
Control techniques
with proper use of control techniques, an experiment has internal validity by eliminating alternative explanations
Holding conditions constant
the only thing we allow to vary across groups are IV conditions - everything else should be the same for the groups of the experiment
ex. how a brain area is defined, what constitutes an AUD
Balancing
when things must vary across groups, make sure that they are equal on average so as to not be biased; necessary because some variables cannot be held constant
ex. individual ages, time of day the scanning is done
Random groups designs
- done irrespective of the individual or time, only done in relation to the conditions
- can be done with various methods, e.g. coin flips, pulling names out of a hat, random number generating
- establishes proper time order relationships for casual inference
- balances subject characteristics
- any differences between groups on dependent variable are caused by independent variable (if no confounds)
Block randomization
a “block” is a random order of all conditions in the experiment
ex. a random order of conditions A, B, C could be B C A
- 1st participant assigned to condition B
- 2nd participant - condition C
- 3rd participant - condition A
Threats to internal validity
ability to make casual inferences is jeopardized when
- intact groups are used
- extraneous variables are not controlled
- selective subject lost occurs
- demand characteristics and experimenter effects are not controlled
Intact groups
- these groups exist before experiment, members interact
- individuals are not randomly assigned to intact groups
- when intact groups (not individuals) are randomly assigned to conditions, subject characteristics are not balanced
- do not use intact groups for casual inference
Extraneous variables
practical considerations when conducting an experiment may create confounding, i.e. if systematically different
control by balancing and holding conditions constant
Subject loss
occurs when participants fail to complete an experiment
mechanical subject loss
when equipment failure or experimenter error results in participant’s inability to complete experiment
- often due to chance factors so likely to occur equally across conditions
- because mechanical subject loss is unbiased, it does not threaten internal validity of experiment
Selective subject loss
occurs when participants are lost differentially across conditions, some characteristic of participant is responsible for the loss, and the subject characteristic is related to the IV or DV
Demand characteristics
cues participants use to guide their behavior in a study
Placebo control group
used to assess whether participants’ expectancies contribute to outcome of experiment
- participants receive a placebo (inert substance), but believe they may be receiving an effective treatment
double-blind experiment
procedures in which both participants and experimenters/observers are unaware of the condition being administered; controls both demand characteristics and experimenter effects
Matched group designs
when random assignment is not possible because only small samples are available
Procedure for matched groups design
- select matching variable (individual differences variables are characteristics of people that differ, or vary; choose matching variables related to outcome or dependent variable)
- measure variable and order individuals’ scores
- match pairs (or triples, quadruples, etc. depending on number of conditions) of identical or similar scores
- randomly assign participants within each match to the different conditions
Important points about matching
- participants are matched only on the matching variable
- participants across conditions may differ on other important variables
- these differences may be alternative explanations for study’s results (confounding)
- the more characteristics a researcher tries to match, the harder it will be to match
Natural groups designs
psychologists’ questions often ask about how individuals differ, and how these individual differences are related to important outcomes
- grouping based on subject characteristics, so group membership exists prior to the start of the study
- when a researcher investigates an independent variable in which the groups (conditions) are formed naturally
- individual differences (subject) variables
- allow researchers to describe and predict relationships among individual differences variables and outcomes; do not allow them to make casual inferences about individual differences variables
Increasing external validity
- include characteristics of situations, settings, and populations to which researchers wish to generalize
- field experiments
- partial replications
- conceptual replications
Statistical analysis
we rely on it to claim an independent variable produced an effect on a dependent variable and rule out the alternative explanation that chance produced differences among the groups in an experiment
Replication
best way to determine whether findings are reliable; repeat experiment and see if same results are obtained
Analysis of experimental designs
Check the data
- errors? outliers?
Describe the results
- descriptive statistics such as means, standard deviations
Confirm what the data reveal
- inferential statistics
