Chapter_5-7.docx

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Department
Psychology
Course
PSYB01H3
Professor
Anna Nagy
Semester
Summer

Description
Chapter 5 The most common measurement strategy is to ask people to tell you about themselves Rate your overall happiness You can also directly observe behaviours How many mistakes did someone make Psychological and neurological responses can be measured as well. Example: heart rate, muscle tension Reliability of measures Reliability refers to the consistency or stability of a measure of behaviour a reliable test would yield the same result each time the results should not fluctuate from one reading to the next if there is fluctuation there is an error in the measurement device Every measurement has two components: 1.True score: the real score on the variable 2.Measurement error Example: If you administer a highly reliable test multiple times, the scores on them might be 97-103; however if you used an unreliable test the scores might be 85-115. The measurement error in the unreliable test is revealed in the greater variability shown in the scores Using unreliable measurements is a waste of time because the results will be unstable and are unable to be replicated We can assess the stability of measures using correlation coefficients o The most common correlation coefficient when discussing reliability is the "Pearson product-moment correlation coefficient" Symbolized as "r" Range from 0.00 to +1.00 and 0.00 to -1.00 0.00 means that the variables are not related at all +1.00 means that there is a positive relationship While -1.00 means there is a negative relationship Test-retest reliability: assessed by measuring the same individuals at two points in time o If many people have similar scores we can say that the measure reflects true scores rather then measurement error 0.80 is how high the correlation should be before we accept the measure as reliable Internal consistency Reliability The assessment of reliability using responses at only one point in time, because all items measure the same variable they should yield similar or consistent results o An indicator of internal consistency is "split-half reliability" Split-half reliability: this is the correlation of an individual's total score on one half of the test with the total score on the other half oThe final measure will include items from both halves The combined measure will have more items and will be more reliable than either half by itself oDrawback of this is that it does not take into account each individual item's role in a measure's reliability. (each question on test is called an "item") Cronbach's alpha: is based on individual items and is another indicator of Internal consistency Reliability oCorrelates each item with every other item oThe value of alpha is the average of all correlation coefficients Item-total correlations: examines the correlation between each time and the total score Since cronbach's alpha and item-total correlations look at the individual items, items that do not correlate with the other items are removed to increase reliability Interrater reliability A single rater might be unreliable but more the one will increase reliability The degree to which raters agree in their observations is interrater reliability o A commonly used indicator of interrater reliability is called Cohen's kappa Reliability and accuracy of measures Accuracy and reliability are totally different o Example: A gas station pump puts the same amount of gas in your car every time, therefore the gas pump gauge is reliable. However the issue of accuracy is still open. The only way you can know the accuracy is to compare how much the pump gives you to a standard measure of a litre. Construct Validity of measures Construct validity: the adequacy of the operational definition of variables o To what extent does the operational variable reflect the true theoretical meaning of the variable o Construct validity is a question of whether the measure employed actually measures the construct it is intended to measure Indicators of construct validity Face validity: the evidence for validity is that the measure appears "on the face of it" to measure what it is supposed to measure. o Do the procedures used to measure the variable appear to be an accurate operational definition of the theoretical variable? Criterion-oriented validity: relationship between scores on the measure and some on criterion o There are 4 types of criterion-related research approaches that differ in the type of criterion that is employed 1. Predictive validity: scores on the measure predict behaviour on a criterion measured at a time in the future o Example: LSAT test predicts how well you'll do in law school 2. Concurrent validity: scores on the measure are related to a criterion measured at the same time o To see whether two or more groups of people differ on the measure in expected ways 3. Convergent validity: scores on the measure are related to other measures of the same construct o One measure of shyness should correlate with another shyness measure or a measure of a similar construct such as social anxiety 4. Discriminant validity: scores on the measure are NOT related to other measures that are theoretically different o Seeing if there are correlations between shyness test results and aggressive/forcefulness test results Research on personality and individual differences Systematic and detailed research on validity is most often carried out measures of personality and individual differences NEO personality Inventory (NEO-PI) o Measures the 5 major dimensions of personality: neuroticism, extraversion, openness to experience, agreeableness and conscientiousness Reactivity of measures Reactivity is a potential problem when measuring behaviour o A measure is said to be reactive if awareness of being measured changes an individual's behaviour Reactive measures don't tell you how the subject behaves under natural settings You can minimise reactivity by letting the subjects get used to the recording equipment or to the presence of the observer Nonreactive or unobtrusive measures involve clever ways of indirectly recording a variable Variables and measurement scales Each variable that is studied must be operationally defined o The specific method used to manipulate or measure the variable There must be at least two values or levels of the variable o Levels can be conceptualized as a scale that uses one of four kinds of measurement scales: o Nominal: no numerical or quantitative properties o Sometimes called "categorical variables" o Example: male/females o Impossible to define any quantitative values o Ordinal: rank ordering; numeric values limited o Example: 1-5 star restaurants o Intervals between items not known 3. Interval: numeric properties are literal; assume equal interval between values
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