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Psychology 124, Week 5 Notes

by: Layne Franklin

Psychology 124, Week 5 Notes PSY 124 - 03

Marketplace > University of Indianapolis > Psychlogy > PSY 124 - 03 > Psychology 124 Week 5 Notes
Layne Franklin
GPA 2.9

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About this Document

These notes may cover some material that will be on the exam.
Fndtns/Psyc Science I:Methods
Jordan Sparks Waldron
Class Notes
Psychology 124
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This 3 page Class Notes was uploaded by Layne Franklin on Friday February 12, 2016. The Class Notes belongs to PSY 124 - 03 at University of Indianapolis taught by Jordan Sparks Waldron in Fall 2015. Since its upload, it has received 22 views. For similar materials see Fndtns/Psyc Science I:Methods in Psychlogy at University of Indianapolis.


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Date Created: 02/12/16
Reliability  Measurement error reduces reliability of a measure.  Reliability  How consistent or dependable is the measure?  The reliability of a measure is an inverse function of measurement error.  Reliability =  Variance in observed scores due to True Scores / Total Variance in observed scores Measurement Error  Observed Score  True Score + Measurement Error  True Score  Participant’s score if the measure was perfect.  Measurement Error  Variability in observed scores due to extraneous factors.  Total Variance in Observed Scores = Variance due to True Scores + Variance due to Measurement Error  Systematic Variance + Error Variance  Many different potential sources of error Assessing Reliability  Correlation Coefficient  Expresses the strength of the relationship between two variables  Test-Retest Reliability  Consistency of participants’ responses on a measure over time.  If characteristic being measured is supposed to be stable, should be high correlation between scores at Time 1 with scores at Time 2  Interitem Reliability  Consistency among items on a scale (measures with more than one item where a composite summary score is created)  Including items that aren’t measuring what they should be increases measurement error.  Item-Total Correlation (1 item compare to sum of the rest)  Split-Half Reliability (Set of items compared to another set)  Interrater Reliability  Consistency between two or more researchers who observe and code participants’ behaviors.  Examine the degree of agreement among raters  We want observers to make similar ratings Validity  Validity  The degree to which a measurement procedure actually measures what it is intended to measure rather than measuring something else.  Measures can be highly reliable but not valid.  A reliable clock tells us that it is 2pm every day at the same time.  A valid clock tells us that it is 2pm when it is actually 2pm.  What about vice versa? Assessing Validity  Face Validity  Do the questions in our measure LOOK like they are measuring what they are supposed to measure?  Construct Validity  Does the measure of a hypothetical construct relate as it should to other measures?  Convergent – correlate with the measures that it should  Discriminant – not correlate with the measures that it should not  Criterion Validity  Does the measure allow us to distinguish among participants on the basis of a particular behavioral criterion?  Concurrent Validity  Predictive Validity Bias in Measurement  Test Bias  A measure is not equally valid (or reliable?) for different groups.  More error in how a test measures for members of a particular group  Race, ethnicity, gender, age, etc.  Just because there are gender, racial, or ethnic differences in a measure does not mean that bias exists.  True differences between groups may exist.  Examples of bias  Ways to investigate bias  Avoid the arm chair analysis!


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