FINAL EXAM

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75 Terms

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observational research

when a researcher watches or monitors participants (people or animals) and systematically records their behavior

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naturalistic

observation “in the wild”

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controlled

observation in controlled setting such as lab

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observer bias

refers to when observers’ expectations influence their interpretation of the participants’ behaviors or outcomes in the study

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minimize observer bias by

having very specific coding criteria that observers are trained to use, multiple raters, masked design

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multiple raters

ensures a check on rating reliability

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inter-rater reliability

computed from pairs of ratings, typically based on a subset (15-20%) of the data

typical guidelines for assessing reliability:

0-0.2 = poor agreement

0.3-0.4 = fair agreement

0.5-0.6 = moderate agreement

0.7-0.8 = strong agreement

>0.8-1 = almost perfect agreement

>.7 or above is preferable for any publishable study

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setting differences between raters

quantitative approach- average ratings

raters discuss where disagreements were made and decide what score to use

an independent third raters that would moderate between raters and decide what score to use

whatever is done, this should be reported in the methods

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blinded design

the observer is unaware of predictions and/or conditions in which the participants are in

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observer effects

refer to when observers’ expectations influence how they behave towards participants

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reactivity

refers to the tendency of participants to act differently if they know they are being observed

not the same as observer effects- the observer isn’t cuing a specific behavior

the mere presence of observation alters behavior of the participant

naturalistic observation is intended to decrease reactivity

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minimize reactivity by

blending in by unobtrusively observing, wait until participants are used to being observed, measure behavior outcomes (measures that behavior occurred rather than directly observing behavior)

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pros of survey research

best if the perspective of the self is of interest, it’s possible to accurately self-report a behavior, using open-ended responses to get to know the phenomenon

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pros of observation research

allows measurement of behavior that otherwise would be hard to access from self-perspective

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cons of observation research

difficult and likely much more time consuming

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Dr. Ewell, a developmental psychologist, is planning on conducting a study that involves watching children play together to determine how sharing behavior occurs in same-sex friend pairs compared to opposite-sex friend pairs. Dr. Ewell is concerned that the children will behave differently because of the presence of research assistants. He is concerned about:

reactivity

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imagine that Dr. Ewell calculates a correlation (e.g., ICC) for his two raters. Which of the following would be the best value for Dr. Ewell to find?

0.89

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surveys (or polls)

are a method of gathering information from participants via self report

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online surveys

always available

in response to a choice (e.g., purchase, attend event)

study participation

federal agency data for population

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in-person questionnaire

study participation

in response to a choice or event (e.g., purchase, attendance at event)

assessment for services

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interview survey

study participation

in response to a choice or event (e.g., stressful life event, natural disaster)

assessment for services

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construct validity of a survey depends on a good match of

the type of information needed, with the feasibility of self-report in your target population

quality of the questions

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self-reports are ideal for

what people think they are doing

what people think they remember

what people think is influencing their behavior

experiences only accessible to the person (e.g., the content of a dream or memory)

attitudes and judgments

exploring a question because the method is low cost

accessing a large and representative sample that spans multiple geographic locations

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self-reports are not good for

precise analysis of behavior

precise details or confidence for memories of events

what may actually be influencing their behavior

when self-report not possible for a population (e.g., infants)

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open-ended questions

allow the participant to fill in the response in any way they like

they provide rich data, but they can be hard to code

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open-ended questions should be used when

sensitive or socially disapproved behaviors

research questions on the explicit content of a self-generated response or information implicit in the response

preliminary research

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leading questions

elicit bias by using non-neutral words in framing question

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double-barreled questions

ask two+ questions in one

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negatively worded questions

often difficult to interpret, especially with likert scales

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participant’s perspective

consider to improve validity of self-report data

shortcuts and biases, social desirability

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response sets

when participants give consistent responses across questions to save time, rather than accurately answering each question

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social desirability

refers to when participants may respond in a way they think is socially desirable

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biased vs. representative samples

biased samples: unrepresentative, some members of the target population have a higher probability of being included in the sample compared to other members

representative samples: based on probability sampling, every member of the population of interest has an equal chance of being selected for the sample

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convenience sampling

researcher requests volunteers from a group who meet general criteria but are recruited in a variety of “non-random” ways

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purposive

researchers target or hand-pick participants that meet specific criteria based on knowledge of the research question

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snowball

variant of purposive, but now participants are asked to recommend others they know that would also meet criteria

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self-selected samples

sampling only those who invite themselves

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simple random sampling

random draw from sample frame

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systematic sampling

pick first participant at random, then call contact every nth person

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cluster sampling

sample from pre-existing sub-groups of your target population

sub-groups sampled from are chosen randomly from all possible sub-groups

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stratified random sampling

researcher selects particular demographic categories on purpose and then randomly selects participants within the categories

allows you to force a match of your sample demographic to the population by randomly drawing within population “strata”

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oversampling

researcher intentionally over-represents one or more groups in order to get an accurate estimate from them

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correlations tell us that

two variables are linearly related and how strong this relationship is

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effect size allows us to compare

correlations across measures of different scales

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bivariate

doesn’t account for third variables

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the least squares regression equation

knowt flashcard image
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errors in prediction based on our regression line are minimized using a

least squares method

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regression equation

describes the numeric relationship between the variables

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predicts a dependent variable (DV) with one independent variable (IV)

knowt flashcard image
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multivariable regression

each predictor variable (X) gets a beta weight (b) that reflects in relationship with Y

<p>each predictor variable (X) gets a beta weight (b) that reflects in relationship with Y </p>
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root mean squared error

average amount of predictive error for regression in the sample, expressed in units of the Y variable

indication of good model fit: lower, because this is amount of error in predicted Y

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RMSE answers

after we use X to predict Y, how much variability is left in Y?

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R2

the proportion of the total variability in one variable that is predictable from its relationship with the other variable

indication of good model fit: higher, because higher values reflect more variability of Y accounted for by predictor variables

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R2 answers

how much variability in Y did the regression explain with X?

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when R2 = 0

variability of Y around the mean of Y (total variability in Y)

variability of Y around the regression of predicting Y from X

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when R2 = 1

variability of Y around the mean of Y (total variability in Y)

variability of Y around the regression of predicting Y from X

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when you have one predictor variable

squaring the correlation coefficient gives you R2

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sum of squares of Y given X

sum of squares for predictive errors

indication of food model fit: lower, because this is unexplained variability in Y after accounting for X

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interpretation template

For every 1 unit increase in X, there there is a change in Y by beta, even even after statistically controlling for (i.e., holding constant) ___. Overall, the model accounts for R2 % of variability in the exam performance.

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interpreting the strength of evidence for

causality from correlational studies

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necessary to interpret the beta

estimated difference in outcome for 1 level difference of predictor variable

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external validity

refers to the degree to which a claim generalizes to a larger population or to other situations

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third variables

“nuisance” variables, outside variables

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moderators

grouping, answers “for whom”

modifies the strength of the association between the independent (X) variable and the dependent (Y) variable

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informs external validity

to which people and situations does the relationship apply to

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mediators

mechanisms, answers “why”

help explain the association between two variables that have an existing correlation, because the mediator variable arises from or is internal to the independent (X) variable

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informs internal validity

by answers how variable X might cause a change in variable Y

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decisions that help for maximize internal validity

often hurt external validity because they limit the population and situations studied

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decisions that help you maximize external validity

often require large sample sizes and heterogeneity in types of people and situations examined

it is more difficult to conduct highly controlled experiments with large samples and in different situations

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steps in testing mediation

  1. is beta coefficient significant for path c?

  2. is beta coefficient significant for path a?

  3. is beta coefficient significant for path b?

  4. regression

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direct replication

same concepts

same operational definitions

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conceptual replication

same concepts

different operational definitions

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replication + extension

same concepts

plus some new concepts

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goals of theory-testing mode

internal validity

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goals of generalization mode

external validity