Research Methods Review 2

internal validity

Is there a potential extra variable that is associated with both A & B, indepently

Confounding Variables

any difference between the experimental and control conditions, except for the independent variable, that might affect the dependent variable

random selection

A way of ensuring that a sample of people is representative of a population by giving everyone in the population an equal chance of being selected for the sample

random assignment

assigning participants to experimental and control conditions by chance, thus minimizing preexisting differences between those assigned to the different groups

Counterbalancing

Switching the order in which stimuli are presented to a subject in a study

Matching

In connection with experiments, the procedure whereby pairs of subjects are matched on the basis of their similarities on one or more variables, and one member of the pair is assigned to the experimental group and the other to the control group.

time lag

needed to wait longer before contining with an experiment to allow time to go back to a normal state

double-blind procedure

an experimental procedure in which both the research participants and the research staff are ignorant (blind) about whether the research participants have received the treatment or a placebo

Partial-blind procedure

Researchers know who is part of what group but doesn't say

Placebo

something which has a positive mental effect, but no physical effect

Condtions

levels of independent variable

Experimental variable

manipulated

Participant Variable

Individual Differences

Control variable

any variable that an experimenter holds constant

between-subjects design

A research design in which different groups of participants are randomly assigned to experimental conditions or to control conditions.

within-subjects design

participants are exposed to all levels of the independent variable

mixed design

an experimental design that combines within-subjects and between-subjects methods of data collection

advantages of within subjects design

Participants in your groups are equivalent

Give researchers more power to notice differences between conditions

Requite fewer participants than other designs

disadvantages of within subjects design

potential for order effects

experiencing all levels of the independent variable changes the way participants act

practice effects

Improvements in performance resulting from opportunities to perform a behavior repeatedly so that baseline measures can be obtained.

carryover effects

when previous treatment alters the behavior observed in a subsequent treatment

order effects

occur when the order in which the participants experience conditions in an experiment affects the results of the study (solution is counterbalancing)

construct validity

How well the DV was measured and how well the IV was manipulated

Pilot Study

a trial run in survey research

ceiling and floor effects

Measurement problem whereby the researcher cannot measure the effects of an independent variable or a possible interaction effect because performance has reached a maximum (or minimum) in any condition of the experiment.

Design Confounds

another variable accidentally varies systematically along with the IV

Crossover Interactions

x-shaped interactions

spreading interaction

- lines not parallel, do not cross over ( treat and no treat/ say something and say nothing)

- one line flat, one line increase or decrease but never cross

external validity

extent to which we can generalize findings to real-world settings

Main Effect

In a factorial design, the overall effect of one independent variable on the dependent variable, averaging over the levels of the other independent variable.

Interaction Effect

a result from a factorial design, in which the difference in the levels of one independent variable changes, depending on the level of the other independent variable; a difference in differences

Interactions show moderators

-Using factorial design to test limits is called "testing for moderators"

independent groups factorial design

Different participants are assigned to each condition.

within groups factorial design

Both independent variables are manipulated as within groups. If the design is 2 x 2, there is only one group of participants, but they participate in all four combinations (or cells) of the design.

mixed factorial design

A design that includes both independent groups (between-subjects) and repeated measures (within-subjects) variables.

simple regression

estimates the relationship between the dependent variable and one independent variable

Multiple Regression

a statistical technique that computes the relationship between a predictor variable and a criterion variable, controlling for other predictor variables

Path Analysis

Estimates casual relationships among several variables simultaneously

Uses images to test causality by comparing it to actual data

Computer Adaptive Testing (CAT)

Test which measure some trait by narrowing down scores by adapting to the user's performance

experience sampling

Looking at the pattern of any variable over the course of multiple measurements

Aggregation

Taking data at one level of analysis and creating scores at higher levels of analysis made up of the individual level information

meta-analysis

The quantitative synthesis of previous empirical work within a given research domain in a systematic fashion

Looks at overall effects, and moderators, and is more generalizable

bivariate correlation

an association that involves exactly two variables

Bivariate Relationship

Not necessarily casual

Range (restrictions) important

Directionality

Confounds and Third Variables

Statistical Significance

a statistical statement of how likely it is that an obtained result occurred by chance

Effect Size

the magnitude of a relationship between two or more variables

Outliers

Numbers that are much greater or much less than the other numbers in the set

restriction of range

results are muddied due to the lack of inability to see the distribution of scores

curvilinear relationship

correlations like straight lines

multivariate design

involving more than two measured variables

Covariance

as A changes, B changes

temporal precedence

A comes first in time, before B

Mediators

extraneous variables that come between the independent and dependent variables

Moderators

when one extra variable applies for one variable but isn't a factor in another one

Case Studies

study of a single person or event

Leading Questions

questions that predispose a respondent to answer in a certain way

double-barreled questions

questions that attempt to get at multiple issues at once, and so tend to receive incomplete or confusing answers

negatively worded questions

a question in a survey or poll that contains negatively phrased statements, making its wording complicated or confusing and potentially weakening its construct validity

response sets

responding in a consistent manner

Acquiescence Bias

The tendency to agree rather than disagree with items on questionnaires.

fence sitting

playing it safe by answering in the middle of the scale for every question in a survey or interview

quasi experiments

participants are naturally occuring or cannot be randomly assigned to groups

wait-list design

when everyone would benefit from treatment

interrupted time series design

A quasi-experiment in which participants are measured repeatedly on a dependent variable before, during, and after the "interruption" caused by some event.

Regression to the mean

If the first measurement is extreme, second measurement will be closer to the mean

attrition threat

people leaving the study

testing and instrumentation biases

same scale usage can cause the same response

Qualitative Sampling

The process of selecting a small number of individuals for a study in such a way that the individuals chosen will be good key informants (reflective and thoughtful, good communicators, comfortable)

Quantitative sampling

generalize from a small sample to a larger population