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Stats and research Flashcards

1
Q

idiographic

A

single subject

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2
Q

nomothetic

A

group studies

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3
Q

AB design problem

A

threat of history - hard to tie intervention to change

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4
Q

ABAB design problems

A

protects against threat of history
threat of failure to return to baseline
ethics of stopping intervention

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5
Q

analogue research vs. clinical trial

A

less generalizability vs methodological compromise

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6
Q

cross sectional design problem

A

cohort effect

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7
Q

longitudinal problems

A

expensive, attrition rate

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8
Q

cross-sequential research

A

combine longitudinal and cross sectional

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9
Q

proportional sampling

A

randomly selected in proportion to representation

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10
Q

systemic sampling

A

every nth random

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11
Q

cluster sampling

A

naturally occurring groups, but everyone within the groups

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12
Q

Threats to internal validity

A

anything other than IV causing change in DV (history, maturation, test practice, instrumentation)

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13
Q

Solomon four-group design

A

Corrects for test practice
pre/post vs. post only
intervention vs. no intervention

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14
Q

Instrumentation

A

threat to internal validity
change in observer or equipment resulting in change to DV. Correct with control group

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15
Q

Statistical regression/ regression to the mean

A

extreme scores get less extreme
manage with control group

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16
Q

selection bias

A

correct with random assignment

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17
Q

attrition/experimental mortality

A

problem if differential in group dropout rates
Compare groups who drop out with t tests

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18
Q

Diffusion

A

no-treatment group gets some treatment indirectly

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19
Q

Experimental expectations/ Rosenthal effect

A

Experimenter transmit clues. correct with experimenter blindness

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20
Q

Demand characteristics

A

features of procedures that suggest expectations to participants

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21
Q

John Henry effect/compensatory rivalry

A

control group work harder to compete with experimental group. Try to keep control and experimental group unaware of each other.

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22
Q

Threat to external validity

A

sample characteristics, stimulus characteriastics, contextual characteristics

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23
Q

Sample characteristics

A

diff between sample and pop

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24
Q

Stimulus characcteristics

A

features of study associated with intervention

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25
Contextual characteristics
conditions in which intervention embedded. Reactive/Hawthorn effect
26
Threats to statistical conclusion validity
low power, unreliability, variability in procefures,. subject heternogeity.
27
positive skew
peak to left
28
neg skew
peak to right
29
standard error of mean
all possible means from random assignment groupings, how far they deviate from middle
30
Central limit theorem
31
Rejection region / region of unlikely value
area corresponds to
31
Type 1 error
mistakenly rejecting Ho proportionate to alpha
32
Type 2 error
mistakenly adopt Ho Inverse with alpha
33
Choosing based on DV
non-parametric if nominal/ordinal parametric - t-test, anova 1+ DV - MANOVA
34
independent vs correlated data
independent if randomly assigned, or based on existing categories (e.g., gender) Correlated if same-subject repeated measures, matched to groups, inherent relationships between ppl in each group
35
parametric test assumptions
interval or ratio data homoscedascity - -similar variance between groups normally distributed data
36
chi square test assumptions
independent observations - no repeated measures
37
Degrees of freedom
possible variations in outcome Chi square: groups -1 Multiple chi square: (rows-1)*(columns-1) Single sample t-test: N-1 Matched/correlated t-test: #of pairs -1 T-test for independent groups: N-2 single ANOVA: N-1, #of groups -1,
38
post-hoc tests
scheffe, then tukey are best for protection from type 1 Fisher's LSD best for proection from type 2 vice versa
39
two-way anova benefit
allows analysis of interaction effects F ratios for each IV and each interaction interaction effects must be examined first
40
MANOVA vs multiple ANOVAs
reduce type 1 error
41
coefficient of determination
correlation coefficient squared, explains variability in Y accounted for by X
42
Simple regression line of best fit
uses least squares criterion
43
assumptions for bivariate correlations
linear relationship between x and y, homoscedascity, unlimited ranges for x and y
44
eta
use when X and Y relationship is curvilinear
45
Multicollinearity
multiple predictors in multiple regression are highly correlated with each other/redundant
46
stepwise regression
computer generated forward - add one predictor at a time until no change to r2 backward - remove one predictor at a time, weakest first, until there is change to r2 Fewest possible predictions
47
higerarchical regression
examiner adds predictors by hand according to theoretical model
48
Canonical R
correlation between 2+ IVs and 2+ DVs (predictor set and criterion set)
49
Discriminant function analysis
2+ IV, 1 nominal DV
50
Loglinear/Logit analysis
2+ categorical IV, 1 categorical DV
51
Path analysis
Causality multiple regressions to test causality model
52
structural equation modeling
inferences about casality e.g., LISREL (linear structural relations)
53
Factor analysis
reduce several variables into fewer factors 1st factor always strongest
54
eigenvalue/characteristic root
factor strength 1+ is significant
55
correlation matrix
table of intercorrelations among tests/items
56
orthogonal rotation
produces factors that have no correlations with each other, easy to interpret communality - factor loadings squared and added together
57
oblique rotations
factors are correlated like in real world
58
principal components analysis
no empirical/theoretical guide on communality values produces uncorrelated factors called components 1st factor accounts for most var
59
principal factor analysis
communality value confirmed before analysis
60
Cluster analysis
look for naturally occuring groups of DVs No a priori hypothesis
61
minimum acceptable reliability is
0.8
62
Spearman-Brown prophesy formula
tells how much more reliable test would be if it was longer
63
on timed tests, preferred reliability measure is
alternate tests, then test-retest
64
power test
items of varying difficulty
65
Kuder-Richardson
split-half reliability for dichotomous repsonse formats KR 20 when varying difficulty KR 21 when equal difficulty error due to content sampling, test heterogeneity
66
Cronbach's
67
Interater reliability
Pearson's r, % agreement, Yule's Y, kappa statistic
68
standard error of measurement
SD of normal distribution from tested 100s of times theoretically reliability
69
standard error of estimate
validity SD of normal distribution from being tested 100 of times theoretically on criterion
70
Item characteristic curve
Rel between item score and total score
71
Item response theory
to what extent does specific item correlate with underlying construct
72
cross validation
give test to new sample shrinkage of criterion-related validity coefficient
73
correction for attenuation
calculates how much more valid it would be if predictor and criterion always reliable
74
criterion contamination
happens for subjective criterions, rater informed of subject's predictor scores before assigning criterion ratings
75
ANCOVA
extra/moderator variables partialled out Looking for group diff, not factors
76
Spearman's rho/kendall tau
corr between ordinal variables
77
pearson r
interval/ratio
78
point biserial
corr between true dichotomy and interval/ratio
79
biserial
corr between artificial dichotomy and interval/ratio
80
phi
corr between two dichotomies
81
tetrachoric
corr between two artificial dichotomies
82
Taylor Russel tables
Moderate base rate, low selection ratio, incremental validity
83
slope bias
occur when there is differential validity - i.e., when the validity coefficients for a predictor (e.g., cognitive ability test), differ for different groups. Consequently, the predictor is more accurate for one group than for another.
84
intercept bias
Intercept bias (or unfairness) occurs when the validity coefficients and criterion performance for different groups are the same, but their mean scores on the predictor differ. As a result, the predictor consistently over- or under-predicts performance on the criterion for members of one of the groups.
85

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