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Validity, Reliability, & Sampling Psych 231: Research Methods in Psychology

Validity, Reliability, & Sampling

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Validity, Reliability, & Sampling. Psych 231: Research Methods in Psychology. Errors in measurement. Reliability If you measure the same thing twice do you get the same values? Validity Does your measure really measure what it is supposed to measure??. reliable valid. unreliable - PowerPoint PPT Presentation

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Page 1: Validity, Reliability, & Sampling

Validity, Reliability, & Sampling

Psych 231: Research Methods in Psychology

Page 2: Validity, Reliability, & Sampling

Errors in measurement Reliability

If you measure the same thing twice do you get the same values?

Validity Does your measure really measure what it is supposed to measure??

reliablevalid

reliable

invalid

unreliable invalid

Page 3: Validity, Reliability, & Sampling

Reliability

True score + measurement error A reliable measure will have a small amount of error

Multiple “kinds” of reliability• Test-retest• Internal consistency• Inter-rater

Page 4: Validity, Reliability, & Sampling

Reliability

Test-restest reliability Test the same participants more than once• Measurement from the same person at two different times

• Should be consistent across different administrationsReliable Unreliable

Page 5: Validity, Reliability, & Sampling

Reliability

Internal consistency reliability Multiple items testing the same construct

Extent to which scores on the items of a measure correlate with each other•Cronbach’s alpha (α)•Split-half reliability

• Correlation of score on one half of the measure with the other half (randomly determined)

Page 6: Validity, Reliability, & Sampling

Reliability

At least 2 raters observe behavior

Inter-rater reliability

Extent to which raters agree in their observations• Are the raters consistent?

Requires some training in judgment

Page 7: Validity, Reliability, & Sampling

Validity

Does your measure really measure what it is supposed to measure? There are many “kinds” of validity

Page 8: Validity, Reliability, & Sampling

VALIDITY

CONSTRUCT

CRITERION-ORIENTED

DISCRIMINANT

CONVERGENTPREDICTIVE

CONCURRENT

FACE

INTERNAL EXTERNAL

Many kinds of Validity

Page 9: Validity, Reliability, & Sampling

VALIDITY

CONSTRUCT

CRITERION-ORIENTED

DISCRIMINANT

CONVERGENTPREDICTIVE

CONCURRENT

FACE

INTERNAL EXTERNAL

Many kinds of Validity

Page 10: Validity, Reliability, & Sampling

Construct Validity

Usually requires multiple studies, a large body of evidence that supports the claim that the measure really tests the construct

Page 11: Validity, Reliability, & Sampling

Face Validity At the surface level, does it look as if the measure is testing the construct?

“This guy seems smart to me, and

he got a high score on my IQ measure.”

Page 12: Validity, Reliability, & Sampling

Internal Validity

Did the change in the DV result from the changes in the IV or does it come from something else?

The precision of the results

Page 13: Validity, Reliability, & Sampling

Threats to internal validity

History – an event happens the experiment Maturation – participants get older (and

other changes) Selection – nonrandom selection may lead to

biases Mortality – participants drop out or can’t

continue Testing – being in the study actually

influences how the participants respond

The precision of the results

Page 14: Validity, Reliability, & Sampling

External Validity

Are experiments “real life” behavioral situations, or does the process of control put too much limitation on the “way things really work?”

Page 15: Validity, Reliability, & Sampling

External Validity Variable representativeness

Relevant variables for the behavior studied along which the sample may vary

Setting representativeness Are the properties of the research setting similar to those outside the lab (Ecological validity)

Subject representativeness Characteristics of sample and target population along these relevant variables

Page 16: Validity, Reliability, & Sampling

Sampling

Why do we do we use sampling methods? Typically don’t have the resources to test everybody, so we test a subset

Page 17: Validity, Reliability, & Sampling

Sampling

Population

Everybody that the research is targeted to be about

The subset of the population that actually participates in the research

Sample

Page 18: Validity, Reliability, & Sampling

Sampling

Sample

Inferential statistics used to generalize back

Sampling to make data collection manageable

Population

Page 19: Validity, Reliability, & Sampling

Sampling Why do we do we use sampling methods?

Goals of “good” sampling:– Maximize Representativeness:

– To what extent do the characteristics of those in the sample reflect those in the population

– Reduce Bias:– A systematic difference between those in

the sample and those in the population

Page 20: Validity, Reliability, & Sampling

Sampling Methods Probability sampling

Simple random sampling

Systematic sampling Stratified sampling

Non-probability sampling Convenience sampling Quota sampling

Have some element of random selection

Susceptible to biased selection

Page 21: Validity, Reliability, & Sampling

Simple random sampling Every individual has a equal and independent chance of being selected from the population

Page 22: Validity, Reliability, & Sampling

Systematic sampling Selecting every nth person

Page 23: Validity, Reliability, & Sampling

Stratified sampling Step 1: Identify groups (strata) Step 2: randomly select from each group

Page 24: Validity, Reliability, & Sampling

Convenience sampling Use the participants who are easy to get

Page 25: Validity, Reliability, & Sampling

Quota sampling Step 1: identify the specific subgroups Step 2: take from each group until desired number of individuals

Page 26: Validity, Reliability, & Sampling

Next time Read: Chpt 8