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Chapter 5

PSYB01 Textbook Notes Chapter 5

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Department
Psychology
Course
PSYB01H3
Professor
David Nussbaum
Semester
Fall

Description
Chapter 5: Measuring Concepts Operationally Defining variables o Every variable must have Operational definition: method used to manipulate or measure the variable being studied • Operational defining relationship’s duration  must specify time frame: is your interest in day, year, months? • Operational defining relationship’s satisfaction  ppl rate their satisfaction using scales • Operational definition’s quality differ based on reliability and validity Self-Report Tests and Measures o Systematic and detailed research on reliability and research is mostly done with self- reports. o Self-reports measure psychological attributes, abilities and potential • NEO Personality Inventory, NEO-PI: self-report to measure 5 major personality dimensions • Clinical/applied settings = MMPI-II, for clinical diagnosis • Career-choice decisions: Vocal Interest Inventory etc. o Use pre-existing measures and not own bc they’re reliable and backed up with valid data to help you decide which measures to use • Allows you to compare findings w/ prior research of the same measure • Knowing concepts of reliability and validity lets you evaluate quality of existing measures and chose operational definitions you create Reliability of Measures o Reliability: the consistency/stability of a measure of B. This is the first step to a good operational definition • a reliable measure (eg. Intelligence) yields same results every time it’s tested • fluctuation in measures = error in measurement device o True Score and measurement error = 2 concepts to understanding reliability • True score: person’s real score • Measurement error: Reducing error/variability = reduces uncertainty = increase reliability − A test w/ least variability is more reliable. It contains less measurement error than a test that has more variability in measures taken throughout duration of time. − It’s important that the measures be reliable bc you can mostly test ppl once. So, it has to be close to accurate that 1 time. − Unreliable measures = meaningless concl bc yield unrepeatable results • To make reliable measures, observe it multiple times. Thus, reliability increases when the number of items increases. − Eg) personality scale has 10+ Qs designed to asses ONE trait • Correlation coefficient (the number that tells us how strongly 2 variables are related) asses the stability of measures • Pearson product-moment correlation coefficient (r)  Most commonly used correlation coefficient for stable measures and must show a high positive correlation to concl. reliable measure. − Unrelated variables: r= 0; strongest relationship = ±1 − Positive/negative = direction of linear relationship → Positive linear relationship = high scores for Var1 = high scores Var2 → Negative linear relationship = High scores for var 1 = low score Var 2 Test-Retest Reliability: o You measure the same individual at 2 points in time o Calculate the r, which determines the relationship b/w the 2 tests o If positive, the measure reflects true score, not measurement error o R > 0.80 o Problem w/ this is individuals remember how they responded to test 1 o So, alternate forms reliability: you give 2 different forms of the same test to same individuals at two points in time • Useful for sontant variables: Intelligence is relatively constant/t so test-retest reliability = high − Mood changes so test-retest reliability won’t be appropriate Internal Consistency Reliability o Asses how well a certain set of items relate to each other o Since all items measure the same variable, they should yield similar/consistent results o Test at 1 point in time. o A common indicator of ICR is value Cronbach’s alpha • You calculate how well each item relates to every other item, which produces a large # of interim correlations • This value is based on the avg of these interitem correlations and the number of items in the measure • By providing info of each item, you can eliminate non-correlated items to increase the measure’s reliability • This lets you construct a quick version of a measure for a quick convenient, but reliable test Interrater Reliability o Is the extent to which raters agree in their obs. o So if 2 raters are judging whether b are aggressive, high interrater reliability is obtained when most of the obs result in same judgement • 2 raters, bc more reliable than 1 rater. o A commonly used indicator of interrater reliability is called Cohen’s kappa Reliability and Accuracy of Measures o Just because a test is consistent, it doesn’t mean it is accurate o For example, measuring intelligence with foot-size device. Results are constant each time, but is not an indicator of your INT o This is the difference b/w reliability and accuracy of measures leads is to a consideration of the validity of measures Validity of Measures o Validity = second step to operational definition o Construct validity: adequacy of the operational definition of variables • Construct: denote a variable that is abstract and needs an operational definition (eg. Social anx etc) • So construct validity’s concern: does the measure what it means to measure?  2 ndstep for operational def. Indicators of construct validity o Face validity: The content of the measure appears to reflect the construct being measured • Purely subjective and based on one’s opinion, so it’s insufficient in determining construct val
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