Midterm 2 - Chpt. 5 Flashcards

Question

Discriminant Validity

Answer 1

Not related (ie low or zero correlation) to what it shouldn't relate to - Q: Do people with high scores on your measure randomly vary in how much they show constructs that could be alternative explanations of what your scale is measuring?

Answer 2

Reliability: - Test-retest - Inter-rater - Internal consistency Construct Validity: - Face - Content - Predictive - Concurrent - Convergent - Discriminant External Validity: - Generalizability

Answer 3

Used to study personality traits, clinical counselling, clinical diagnoses Better to use existing measures/scales than your own - Will have reliability and validity data to help decide which measure to use - Also able to compare findings with prior research using the same measure - Can find using Mental Measures Yearbook

Answer 4

- True Score - Measurement Error

Answer 5

person's actual level of the variable of interest

Answer 6

any contributor to a measure's score that is not based on the actual level of the variable of interest - i.e. measuring response time with button pressing (after a beep) Other factors: Someone reacts quickly, but presses the wrong button, then has to react again to press the right button (CONTRIBUTES TO OUR MEASURE OF REACTION TIME, BUT UNRELATED TO WHAT WE'RE TRULY INTERESTED IN) Consider how much measurement error exists in a measure

Answer 7

Excess measurement error makes it hard to detect any true relationship between variables, but cause amounts of true variance being captured is small

Answer 8

ALL measures contain some amount of measurement error Key is to minimize this measurement error and maximize the amount of true score being captured by any particular measure

Answer 9

making multiple observations of the same variable A method normally found in assessing personality traits and cognitive abilities Reliability increases as the number of items increases i.e. a scale with ten or more questions designed to assess the same trait

Answer 10

Can assess the stability of measures using a correlation coefficient: number that tells us how strongly two variables are related to each other

Answer 11

Most common method of calculation being the Pearson Correlation Coefficient Ranges from 0.00 - +1.00 when positive, and 0.00 - -1.00 when negative Lowercase r 0 = no relation Closer to 1 or -1 = strong correlation Can be positively linear or negatively linear

Answer 12

Test-retest reliability is assessed by giving many people the same measure twice - EX: reliability can be assessed by giving it to a group of people on one day and then again a week later - With two scores for each person, you would calculate a correlation coefficient to determine the relationship between the first/second scores No agreed-upon cut-off for determining when a correlation is high enough to be acceptable, but some suggest a test-retest correlation of at least .80

Answer 13

Practice effects - correlations between two scores can become inflated if people are likely to remember how they responded the first time SOLUTION - alternate forms reliability: two different forms of the same test are administered on two separate occasions Some constructs are relatively stable across time - like personality traits Some aren't, and expected to change - like mood Obtaining two measures from the same people at different points can be difficult

Answer 14

Examines how successful the different items in a scale are at measuring the same construct or variable EX: think of each item as a different attempt to measure the same construct - When people respond to similarly across these different attempts, it suggests that the measure is reliable

Answer 15

Cronbach's Alpha Researcher calculates how well each item correlates with every other item, which produces a large number of inter-item correlations Give info about each individual item and its relation to the total score Items that don't correlate with the others can be eliminated to increase measure's reliability While reliability can increase with longer measures, a shorter version can be more convenient to administer and also have accepted reliability

Answer 16

Recently superior alternative - coefficient omega Another form - split-half reality: attempts to determine the degree to which all the items in a scale are related to one another - Split items in a scale into two parts based on some random process, then administering both halves to a group of people - After scoring each half, can calculate a correlation to see how well performance on one half is related to performance on the second half

Answer 17

In some research, raters observe behaviours and make ratings or judgements - i.e. rating the amount of perceived emotion in someone To make these ratings, raters follow a strict set of guidelines in order to make these judgements as systematic as possible - To improve, have more than one person as a rater Reliability of these ratings can be determined by calculating inter-rater reliability: extent to which raters agree in their observations, so if one rater gives a high score for a target, the other ratings also rate this behaviour as high

Answer 18

its measuring what it's intending to measure

Answer 19

Degree to which an experiment is well-designed and can support a causal claim

Answer 20

Construct validity: whether a variable's operationalization is accurate in capturing the intended phenomenon Degree to which the operationalization of a variable reflects the true theoretical meaning of the variable Variables can be measured and manipulated in a variety of different ways, and there is never a perfect operationalization of a variable - Thus, different indicators of construct validity are used to build an argument that a construct has been accurately operationalized and is properly measured by a particular scale

Answer 21

□ How do we know that a measure is a valid indicator of a particular construct? □ We gather construct validity information by examining many different forms of validity - Helps us build an overall case for the broader category

Answer 22

The measure appears, "on the face of it", to measure what it's supposed to measure - whether it appears to asses the intended variable - Involves only a judgement of whether the content of the measure appears to measure this variable; subjective process - i.e. pointless Buzzfeed quizzes - Not efficient enough by itself to conclude that a measure has a construct validity

Answer 23

Evaluated by comparing the content of the measure with the theoretical definition of the construct, ensuring that the measure captures all aspects of the construct and nothing extraneous to the construct - i.e. a construct has 3 different aspects, your scale should try to measure all 3 of these aspects - Focus on assessing whether the content of a measure reflects the meaning of the construct being measured (like face validity)

Answer 24

seeing if the measure can usefully predict some future behaviour that is theoretically related - EX: academic motivation at beginning to predict final grades at the end of term - Grades are the standard or criterion by which we are judging the validity of our measure - Important when studying measures designed to improve our ability to make predictions about different behaviours

Answer 25

similar to predictive validity in that it examines the prediction of a criterion, but instead of a future behaviour it examines a criterion measured at the same time as the measure is administered - One common method is to study whether two or more groups of people differ on the measure in expected ways - i.e. psychopaths versus the general public Another being studying how people who score either low or high on the measure behave in different situations

Answer 26

extent to which scores on the target measure are related to scores on the other measures of the same construct or similar constructs Different measures of similar constructs should "converge", or be related to one another EX: one measure of psychopathy should correlate highly with another psychopathy measure or measures of similar constructs

Answer 27

sort of the opposite of convergent validity, in that it's a demonstration that the measure is not related to variables that are conceptually unrelated to the construct of interest The measure should discriminate between the construct being measured and other, unrelated constructs Scores on the mean should diverge rather than converge with these measurements of unrelated constructs

Answer 28

potential issue with measuring behaviours is that people can behave differently when they know they're being observed People reacting to the act of measurement and changing their behaviour - If this occurs, then we're no longer learning about how someone would behave in the real world, only how they would behave when they know they're being observed Measures of behaviour vary in terms of their potential reactivity

Answer 29

Ways to minimize: - allowing time for people to become used to the presence of the observer or the recording equipment - Measure something without that person noticing or knowing (AKA non-reactive or nonobtrusive operationalizations) - Clever ways of measuring

Answer 30

- Nominal - Ordinal - Interval - Ratio

Answer 31

- research, including conclusions drawn - options available for establishing construct validity - the kinds of statistical analyses that are possible and appropriate to use when analyzing your data

Answer 32

no numerical or quantitative properties Instead, categories or groups simply differ from one another EX: country of birth - people are born in a certain country, and we can classify people based on what country they were born in - Don't have numerical properties, can't be more or less than when it comes to the country of birth: levels are merely different EX: attractive vs not attractive - Doesn't tell you anything about how attractive they find the person, but tells you whether or not they do find them attractive (like a yes or no)

Answer 33

allows us to order the levels of the variable in terms of rank Instead of having categories that are different, the categories can be ordered from first to last - EX: Olympic medals, birth order However, we don't know anything about the distance or difference between each element No particular value Is attached to the intervals between numbers

Answer 34

difference between the numbers on the scale are equal in size - EX: difference between 1 and 2 is the same size as the differences between 2 and 3 - Increases of two (15-17) - Zero doesn't indicate a complete absence of quantity; only an arbitrary reference point - Cannot form ratios based on these numbers (Temperature example)

Answer 35

like an interval scale, except it does have a meaningful absolute zero point that indicates total absence of the variable being measured - Can enable statements such as "a person who weighs 100 kilograms weighs twice as much as a person who weights 50 kilograms) (Not possible with other scales) - Often used with variables involving physical measures