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research methods exam 2 Flashcards

1
Q

self report measurement

A

type of measurement
-participants provide information about themselves through a survey, questionnaire, interviews or even diaries giving responses to pre-set questions
Ex: Likert scale

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2
Q

observational/behavioral measurement

A

type of measurement
-researcher observes & records some behavior
Ex: kids in class, rats in lab

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3
Q

physiological measurement

A

type of measurement
-recording any of a wide variety of physiological processes
Ex: heart rate, pulse, blood pressure, eye tracker

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4
Q

categorical variable

A

scale of measurement
-countable number of distinct groups based on a characteristic
-cannot be ordered or measured numerically
Ex: ordinal

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5
Q

quantitative variable

A

scale of measurement
-represents data in numerical form and these numbers have meaning attached
Ex: ratio, interval

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6
Q

ordinal measurement

A

scale of measurement
-represents categories and groups with a ranking order
-first, second, third
-unequal distance between categories
-no true zero
Ex: education levels, stages of disease, sports ranking, grades (A-F)

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7
Q

interval measurement

A

scale of measurement
-numbers ordered on a scale
-intervals between data points are consistent and meaningful
-no true zero
Ex: temperature, IQ, standardized test scores

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8
Q

ratio measurement

A

scale of measurement
-data on a scale with a true zero
-equal intervals
Ex: height, weight, age, time, distance, test score (0-100), exam (number of correct answers)

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9
Q

face and content validity

A

-does it look like a good measure?
-both face and content validity are subjective ways to assess validity
face: it looks like what you want to measure
content: the measure contains all the parts that your theory says it should contain

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10
Q

criterion validity

A

-does the measure correlate with key behaviors?
-correlational evidence for criterion validity
Ex: NCLEX correlates with being a good nurse
Ex: SAT doesn’t have good criterion validity - it is not directly tied to good/bad results or success in school

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11
Q

convergent & discriminant (divergent) validity

A

-does the pattern make sense?
convergent: test of the extent to which a self-report measure correlates with other measures of a theoretically similar construct
discriminant: test of the extent to which a self-report measure does not
correlate strongly with measures of theoretically dissimilar constructs

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12
Q

test-retest

A

consistent scores every time the measure is used

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13
Q

interrater reliability

A

consistent scores no matter who does the measuring

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14
Q

internal reliability

A

internal consistency; participants provide a consistent pattern of responses, regardless of how the researcher has phrased the question

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15
Q

open ended survey question

A

-allows respondents to answer any way they like
more detail, but more time

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16
Q

forced choice survey question

A

-forces people to choose yes/no or pick the best of 2 or more options
less time, clear answer, but less detail

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17
Q

Likert scale survey question

A

a rating scale containing multiple response options anchored by the specific terms including term “(dis)agree” (strongly agree-strongly disagree)

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18
Q

Likert-type scale

A

basically the same as Likert, but not using the term “(dis)agree”
-can be likeliness, satisfaction, importance

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19
Q

semantic differential format survey question

A

response scale whose numbers are anchored at both ends with contrasting adjectives
Ex: horrible 1 2 3 4 5 fantastic

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20
Q

wording questions

A

-more variations in question wording than type of question

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21
Q

leading questions - questions/wording to avoid

A

-wording encourages one response more than others
-weak construct validity
keywords: “do you agree?”, “wasn’t the…
?”

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22
Q

double-barreled question - questions/wording to avoid

A

-asks 2 questions in 1
-weak construct validity
-confuses people on which question to answer

23
Q

negatively worded questions - questions/wording to avoid

A

-contains negatively phrased statements, making its wording complicated or confusing
-potentially weakens construct validity

24
Q

question order

A

-order in which questions are asked can also affect the responses to a survey
-to fix this: randomize the question order & prepare different versions of a survey with the questions in different sequences

25
Q

response sets (aka nondifferentiation)

A

-always answering the same, not fully reading each question
-happens in long surveys, people want to finish it
-answer consistently with positive, negative or neutral
-to fix this: reverse the question wording

26
Q

acquiescence (yea-saying)

A

-agree with all questions, again without truly reading questions (“strongly agree” or “yes”)
-to fix this: reverse wording of questions

27
Q

fence sitting

A

-consistent answer in the middle, not choosing a side
-occur when people think answers might be controversial or question is confusing/unclear
-to fix this: use forced choice questions & even number scales by removing the neutral/middle option

28
Q

faking good (socially desirable responding)

A

-giving answers on a survey that make people look better than they really are
-people want to look good in the eyes of others & don’t want to give an unpopular opinion
-to fix this: ensure participants of anonymity of responses, ask people’s friends to rate them (because others know us better in domains where we want to look good)
-to fix this: use computerized measures to evaluate people’s implicit opinions about sensitive topics

29
Q

faking bad

A

-giving answers that make one look worse than they really are

30
Q

self-reporting more than they can know

A

more than they can know:
-self-reports can be inaccurate, especially when people are asked to describe why they are thinking, behaving, or feeling the way they do
-when asked, most people willingly provide an explanation/opinion to researchers, but
sometimes unintentionally give inaccurate responses

31
Q

self-reporting memories of events

A

-memories for significant life experiences can be quite accurate, but other times memories might not match the accuracy

32
Q

observation bias

A

-when observers see what they expect to see
-observers’ expectations influence their interpretation of the participants’ behavior or the outcome of the study

33
Q

preventing observer bias & observer effects

A

-use a masked design: observers do not know to which conditions the participants have been assigned & they are not aware of what the study is about

34
Q

observer effects

A

when participants confirm observer expectations
-expectancy effect vs reactivity

35
Q

expectancy effect

A

observers inadvertently change the behavior of those they are observing
-participant behavior changes to match observer expectations

36
Q

reactivity

A

participants reacting to being watched
-can react to be on their best behavior, their worst, or just behave differently

37
Q

population

A

the entire set of people or things in which you are interested

38
Q

sample

A

the smaller set of people/things taken from the population
-intended to serve as an estimation of the population

39
Q

census

A

sampling every member of the population
-has the highest validity, because it represents every person

40
Q

convenience sampling

A

biased method
-sampling only those who are easy to contact
-very common & easy
Ex: professor using students as participants

41
Q

self-selection sampling

A

biased method
-sampling only those who volunteer to participate
Ex: rating something online, online quiz

42
Q

simple random sampling

A

unbiased method
-obtained by putting every member’s name of your population of interest into a pool and then randomly selecting a predetermined number of names from the pool to include in your sample
-NOT random assignment

43
Q

systematic sampling

A

unbiased method
-researchers select members of the population at a regular interval
Ex: I could roll two dice. Let’s say one lands on
two and the other lands on three. I would start
at the second person in the class and then
choose every third person until the sample
reached the desired size

44
Q

simple random & systematic sampling

A

extremely time consuming
not always possible (cannot access population of interest)
very difficult

45
Q

cluster sampling

A

unbiased method
-a probability sampling method in which you divide a population into clusters, such as districts or schools, and then randomly select some of these clusters as your sample
Ex: classes at Assumption, randomly survey 10 classes

46
Q

multistage sampling

A

unbiased method
-a method where researchers draw a sample from a population using smaller and smaller groups at each stage
-this method is often used to collect data from a large, geographically spread group of people in national surveys, for example
-this can be used to break down larger clusters
Ex: all college students - schools - randomly select schools - randomly select classes within schools

47
Q

stratified random sampling

A

unbiased method
-method of sampling that involves the division of a population into smaller subgroups known as strata
-strata are formed based on members’ shared characteristics
-sample represents same proportion of population

48
Q

oversampling

A

unbiased method
-variation of stratified random sampling that selects respondents so that some groups make up a larger share of the survey sample than they do in the population

49
Q

settling for nonprobability/biased sampling techniques

A

-a random sample is not always attainable

50
Q

purposive sampling

A

biased method
-used when you want to study certain kinds of people, so you only recruit those types of participants
Ex: selecting experts or top students to give feedback

51
Q

snowball sampling

A

biased method
-a variation of purposive sampling in which study participants are asked to recommend other participants for the study

52
Q

quota sampling

A

biased method
-similar to stratified random sampling
-the researcher identifies subsets of the population and then sets a target number (quota) for each category in the sample
-then uses nonrandom sampling until the quotas are filled

53
Q

interrogating external validity

A

in a frequency claim, external validity is a priority
-to evaluate claim, evaluate sampling technique
in nonprobability samples (in real world & research studies), external validity is a lower priority

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