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EBP2 > Final > Flashcards

Final Flashcards

1
Q

MCD is a mathematical multiple of ___

A

SEM

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2
Q

______ often used to construct and evaluate scales/questionnaires

A

Internal consistency

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3
Q

Logistic =

A

Use of categorical variables
DV is categorical
Ex: success vs non-success

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4
Q

Which correlation coefficient?

1 ordinal and 1 ratio/interval

A

Spearman’s rho

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5
Q

Kappa interpretation

A

Basically same as ICC
Depends on weights used;
Exactly same as ICC when weights squared

< 0.4 poor-fair

  1. 4-0.6 moderate
  2. 6-0.8 substantial
  3. 8-1.0 excellent
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6
Q

1-way ANOVA

A

Parametric
3 or more independent groups
1 IV with 3 or more levels

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7
Q

Logistic regression

A

Trying to predict a dichotomous variable
Diagnosis (have vs doesn’t have condition)
Outcome of treatment (success vs non-success)

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8
Q

Assumptions of regression analysis

A

Linear relationship = approximation of “true” lone in population

For every X there is a normal distribution of Y (sample data include random samplings from these distributions in Y)

Homogeneity of variance

DV = continuous measure

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9
Q

Discrete (nominal/ordinal) reliability coefficients

A

Percent agreement

Kappa - better

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10
Q

Regression is a __ statistic

Linear relationship =

A

Parametric
Linear relationship = approximation of “true” line in population

For every X there is a normal distribution of Y (sample data includes random samplings)

Homogeneity of variance

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11
Q

Logistic regressions primary outcome ____

A

OR (odds ratio)

Null value is 1 (not 0)

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12
Q

Which correlation coefficient?

All nominal dichotomy

A

Phi coefficient

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13
Q

Linear =

A

Use of continuous variables
DV is continuous
Ex: does age predict BP

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14
Q

Which correlation coefficient?

1 nominal dichotomy, 1 ratio/interval

A

Point biserial

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15
Q

Interpretation of Relative Risk and Odds Ratio scores

A

RR or OR = 1
Null value
No association between exposure and disease

RR or OR > 1
Positive association
Exposure considered harmful

RR or OR < 1
Negative association
Exposure is protective

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16
Q

Kruskal–Wallis ANOVA

A

Dependent variable Ordinal
Can not assume normal distribution
3 or more independent groups
1 IV with 3 or more levels

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17
Q

Coefficient of determination

A

Square of correlation coefficient
Done bc more directly interpretable
“The % of variance in y that is explained - or accounted for- by x”

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18
Q

Reliability is tied to the concept of

A

Measurement error

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19
Q

ICC estimate based on ___ will always be substantially higher than estimate based on ____

A

Average measures always high than single measures

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20
Q

ANOVA of regression

A

Test hypothesis that predictive relationship occurred by chance

If b (slope) = 0, line is horizontal = no relationship

If p < than alpha, reject null and conclude predictive relationship is significant

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21
Q

Paired t-tests

A

Parametric
1 group
1 IV with 2 levels

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22
Q

ICC interpretation showing “good reliability”

A

ICC > 0.75

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23
Q

ICC Model 1

A

Each subject measured by different set of raters; randomly chosen
Rarely used in clinical research

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24
Q

A reliable measure can be expected to

A

Repeat the same score on 2 different occasions provided that the characteristic of interest does not change

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25
Q

Interpretation of correlation coefficients

A
  1. 00-0.25 = little to no relationship
  2. 26-0.50 = fair relationship
  3. 51-0.75 = moderate to good
  4. 76-1.00 = good to excellent

These values are NOT strict cutoff points. Depends on type of research.

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26
Q

Most predictors are ___ scale, but can also use ___. But not ____.

A

Most predictors are continuous scale
Can also be dichotomous or ordinal scale
But NOT multi category nominal (ie race)

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27
Q

ANOVA

Umber of IV and DV

A

IV : more than 1

DV: 1

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28
Q

Rxx (reliability coefficient) will be bigger when

A

True variance is larger

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29
Q

Nonparametric tests are ___% of parametric tests with regard to power

A

65-95% as powerful as parametric equivalent

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30
Q

Reliability coefficient (rxx) ranges ___ meaning

A

Range 0-1
0 = no reliability
1 = perfect reliability

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31
Q

Multiple linear regression

A

More than 1 predictor in the model

Y= a + b1X1 + b2X2 
a = regression constant
b1X1 = 1st regression coefficient x 1st predictor
B2X2 = 2nd regression coefficient x 2nd predictor

Note- there can be more than 2

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32
Q

Hierarchical Linear Modeling (HLM)

A

Linear mixed modeling
For use when data is “nested” within groups
(Students nestled within classroom,
Patients nested within clinics)

Occasions nested within subjects
Treats each subject like a regression line

Analyzes “trajectory” of each subject in each group

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33
Q

Standardized Beta Weights

A

Helpful to know relative contribution of each predictor variable

Impossible to tell with raw regression coefficients (ie b1 May be in years, b2 lbs.)

Raw coefficients transformed into unitless beta weights

Accuracy of prediction

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34
Q

Correlations only applicable for ___ of scores. Correlations quantify strength of ____ only.

A

Pairs of scores

Linear relationships only - based on equation for a straight line.

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35
Q

MANOVA

Number of IV and DV

A

IV = more than 1
DV = more than 1
MANOVA is for analyzing >1 DV simultaneously

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36
Q

Nonparametric stats are based on…

A

Comparisons of ranks of scores

Comparisons of counts (yes/no) or “signs” of scores

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37
Q

Phi coefficient

A

Both variables dichotomous

Ex: gender and group

Worthless scatter plot
Does NOT work with non-dichotomous nominal

Similar to chi-square test (will give same p-value)
But phi gives strength of relationship

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38
Q

Both ____ and ___ give single indicators of reliability that capture strength of a relationship plus agreement in a single value

A

ICC and Kappa

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39
Q

Problem with correlation coefficient (Pearson’s r)

A

Assess relationship, not agreement

Only 2 raters or occasions can be compared

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40
Q

___ gives “unstandardized” estimate of reliability (ie untis of measurement)

A

SEM

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41
Q

Cronbach’s alpha represents correlation ____

A

Among items and correlation of each individual item with the total score

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42
Q

Spearman Rank (rho) correlation coefficient (rs)

A

Nonparametric analog of Pearson’s r

1 continuous, 1 ordinal variable OR 2 ordinal variables

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43
Q

Analysis of residuals to test assumptions
Plot residuals on ___-axis
Predicted values on ___-axis

A

Residuals on y-axis
Predicted values on x-axis

Looking for symmetry

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44
Q

The amount of change in a variable that must be achieved to reflect a true change/difference

A

MDC minimal detectable difference/change

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45
Q

Point biserial correlation (r pb)

A

1 variable dichotomous, 1 variable continuous

Does NOT work with non-dichotomous nominal (ie age and race)

Computationally same as Pearson’s r
Results same as t-test

Ex: gender vs height

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46
Q

CV is unit-less, so helpful comparing ____

A

Variability between 2 distributions on different scales

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47
Q

Logistic regression
DV=
Predictors =

A

DV = dichotomous

Predictors (IV) = continuous, ordinal or dichotomous

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48
Q

We use __ to predict ___ In linear regression

A

X (IV) to predict Y (DV)

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49
Q

3 types of stepwise procedures

A

Forward: start with no predictors, then add

Backward: start with all predictors, then remove

Stepwise: start with no predictors, then add but can also remove

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50
Q

___ is stability of repeated measures over time. Is basically the same as test-retest reliability

A

Response stability

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51
Q

Kappa can be used on __ data

A

Nominal and ordinal

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52
Q

Adjusted R^2

A

Chance corrected R^2
Adjusted down for having more predictor variables

Accuracy of prediction

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53
Q

The % of variance in y that is explained (or accounted for) by x

A

Coefficient of determination

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54
Q

Multicolinearity

A

When Xs in model are substantially correlated with each other
Creates problems with interpretations of b weights

Select independent predictors: not highly correlated w/ each other but highly correlated w/ dependent (predicted) value

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55
Q

Non-parametric:
IV Level of measurement
DV level of measurement
Question

A

IV: nominal
DV: ordinal
Q: ranks different?

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56
Q

Regression line of best fit

A

Error from line = residual
Residuals are squared to eliminate sign and penalize for worse errors

Line with least squared errors = line of best fit

57
Q

_____ uses relationships (correlation) as a basis for prediction

A

Regression analysis

58
Q

Cautions with interpretations of correlation

A

Agreement
Causation
Extreme outliers (can create inflated correlation with only a few extreme data points)
Limits in range if score (can’t generalize beyond range of scores in sample) Liw correlation may be due to limited range.

59
Q

Bias =

A

Mean difference

60
Q

Which correlation coefficient?

All data ratio/interval

A

Pearson r

61
Q

LOA

A

Limits of agreements

Range include ~95% of differences

62
Q

Case-control and cohort studies are of ____ design, and intend to study ___. Generally IV and DV are ___ variables

A

Exploratory design
Intended to study risk factors (assoc between disease and exposure)
Both IV and DV dichotomous

63
Q

Continuous (interval/ratio) reliability coefficients

A 
Pearson correlation (r)
Intraclass correlation coefficient (ICC)- better
64
Q

Outliers effect on regression line

A

Outliers/deviant scores have large effect on regression line

65
Q

Which correlation coefficient?

1 nominal dichotomy, 1 ordinal

A

Rank biserial

66
Q

MANOVA: ___ DV, ___ groups

A

2 or more DV
3 or more groups

MANOVA combines multiple DVs into 1 “combo DV”

67
Q

Cohen’s kappa coefficients used for _____

A

Categorical scale scores

68
Q

Weighted kappa best for ____. Weights can be ___ and ____.

Can choose to make “penalty” ____ for ___

A

Best for ordinal data
Weights can be arbitrary, symmetric or asymmetric
Penalty worse for larger disagreements

69
Q

Interpreting relative risk/odds ratios

A

RR < 1 suggests protective
RR > 1 suggests harmful (positive association)
RR = 1 null/ no association

If 95% CI includes 1 = not significant
If 95% CI excludes 1 = significant

Chi-square:
P-value > 0.05 association not significant
P-value < 0.05 association significant

70
Q

Epidemiology generally uses ___ designs with ___ variables

A 
Observational design 
Dichotomous variables (disease or no disease/ exposed or unexposed)
71
Q

Significance of coefficient: p-value and CI

A

Null hypothesis: the correlation between variable X and variable Y is not significantly different from zero. Ho: r=0

Very sensitive to sample size
Trivial coefficients (r=0.1 to 0.2) are often statistically significant if sample large enough
72
Q

2 related scores

Parametric and Nonparametric tests

A

Parametric: paired t-test
Nonparametric: Wilcoxon signed-ranks test (T)
Sign test

73
Q

Percent agreement is simply ____. Calculate by…

A

How often raters agree

Divide number of agreements by total of all possible agreements

74
Q

Correlation

Number of IV and DV

A 
IV = 1
DV = 1
75
Q

Rank biserial correlation (r rb)

A

1 variable dichotomous (nominal), other variable ordinal

Computationally about same as Spearman’s rank

Ex: gender vs MMT
Results same as Mann-Whitney U-test

76
Q

ICC interpretation p-value tests whether

A

Point estimate is statistically different from 0

77
Q

Stated in terms of variance, reliability =

A

True score reliability
_____________________________
(True score variability + error variability)

78
Q

ICC model 3

A

Ea subject measures by same rater(s);
Raters are only ones of interest
Most common for intra-rater reliability
Can be for inter-rater reliability if study raters only ones of interest

79
Q

Most common correlation coefficient

A

Pearson product-moment correlation coefficient (r)

80
Q

ICC give ______ estimate of reliability (ie no units) and often reported in conjunction with

A

“Standardized”

SEM

81
Q

Relative Risk

A

RR= incidence of disease in exposed individuals/ incidence of disease among unexposed individuals
Used in cohort studies
Quantify strength of association between exposure and disease
2x2 table

82
Q

The first number in ICC type is __ the second number is ___

A

Model

Form

83
Q

ANOVA:
IV Level of measurement
DV level of measurement
Question

A

IV: nominal
DV: continuous
Q: difference between means?

84
Q

Linear regression

Number of IV and DV

A 
IV = 1
DV = 1
85
Q

Correlation coefficient (R) for regression

A

Rough indicator of goodness of good fit for regression line

Same as correlation coefficient (r)

Accuracy of prediction

86
Q

Visual modeling of both direct and indirect relationships.

Can analyze both direct and indirect relationships between….

A

Path analysis
Can analyze both direct and indirect relationships between
1 or more exogenous variables (IV)
1 or more endogenous variables (DV)

87
Q

ANOVA: ____ DV, ____ groups

A

1 DV, 3 or more groups

88
Q

ICC forms

A

2nd number in parentheses represents number of observations used to obtain reliability estimate

89
Q

SEM (std error if measurement) is _____ measure of reliability.
It is ______

A

Absolute
Standard deviation of the distribution of theoretical multiple measurements
It is mathematical multiple of ICC

90
Q

Odds ratio

A

OR= odds of exposure among cases (w/ disease) / odds of exposure among controls (w/o disease)
Used in case-control studies
Quantify strength of association between exposure and disease
2x2 table

91
Q

Regression:
IV Level of measurement
DV level of measurement
Question

A

IV: continuous
DV: continuous
Q: strength of prediction?

92
Q

Observed score is

A

True score +/- error

93
Q

ICC interpretation that is “best for clinical measurements”

A

ICC > 0.90

94
Q

T-tests: number of IV and DV

A 
IV = 1 
DV = 1
95
Q

Correlation coefficients:
Sign indicates ____.
(+) (-)
____ means higher coefficient

A

Direction
+ 1.00 = perfect line: graphed bottom L to top R
- 1.00 = perfect line: graphed top L to bottom R
Tighter grouping means higher coefficient

96
Q

Reliability for categorical scales based on ______. Agreements are ___ and disagreements are ___.

A

Frequency table
Agreements on diagonal
Disagreements are all others

97
Q

ICC model 2

A

Ea subject measures by same raters; raters randomly chosen and representative of rater population
Results generalize
Most common for inter-rater reliability or test-retest reliability

98
Q

Cohort studies. Subjects selected based on ____. Usually ___, but can be ____. Examine ___. Doesn’t work well for ___.

A

Subjects selected based on exposure or not.
Usually prospective, but can be retrospective
Examine if different incidence or disease
Doesn’t work well for rare conditions

99
Q

Nonparametric tests are unable to be performed on…

A

Complex designs like 2x3

100
Q

Stepwise procedures in multiple regression models

A

Criteria set to retain or reject predictors
Predictor with highest partial correlation entered first
Others added/removed in sequence Deleon criteria
Should result in model with greatest parsimony and least multicolinearity

101
Q

ICC (intraclass correlation coefficients) used for

A

Continuous scale scores

But can be used for original data if intervals “assumed” to be equivalent (like a pain scale)

102
Q

Pro and con of MANOVA

A

Pros:
Gets around multiplicity problem (increased type 1 error risk)
Can be more powerful if DVs related

Cons:
“Combo DV” is not directly interpretable
If statistically significant, must follow up with post-hoc ANOVAs

103
Q

Regression coefficient (B)

A

Value/slope in linear equation

Rate of change in Y for each unit change of X

Accuracy of prediction

104
Q

Ratio of std deviation to mean, expressed as a percentage

A

CV coefficient of variation

105
Q

Covariance means

A

As one changes, the other also changes

106
Q

ICC Form 1

A

Only 1 observation per subject per rater (or rating)

107
Q

Problem with percent agreement

A

Does not account for agreement due to chance

Tends to overestimate reliability

108
Q

Multiple linear regression

Number of IV And DV

A 
IV = more than 1
DV = 1
109
Q

2 independent groups

Parametric and Nonparametric tests

A

Parametric: unpaired t-test
Nonparametric: Mann-Whitney U test

110
Q

Correlation:
IV Level of measurement
DV level of measurement
Question

A

IV: continuous
DV: continuous
Q: strength of association?

111
Q

Unpaired t-test

A

Parametric
2 independent groups
1 IV with 2 levels

112
Q

Mann-Whitney U test

A

Dependent variable Ordinal
Can not assume normal distribution
2 independent groups
1 IV with 2 levels

113
Q

3 or more related scores

Parametric and Nonparametric tests

A

Parametric: 1-way repeated measures analysis of variance (F)
Nonparametric: Friedman 2-way analysis of variance by ranks (x^2r)

114
Q

Kappa coefficient is proportion of agreement ____

A

Between raters after chance agreement has been removed

115
Q

Receiver operating characteristics (ROC) used to

A

Find cut off scores (dichotomous data)

116
Q

__ types of ICC depending on

A 
6 ICC types
Depends on:
Purpose of study
Design of study 
Type of measurements
117
Q

Odds ratio and case control studies are selected based on ____, so cant determine ___

A

Selected based on whether they have disease or not,

Can’t determine rate of incidence

118
Q

Wilcoxon sign-ranks test

A

Dependent variable Ordinal
Can not assume normal distribution
1 group
1 IV with 2 levels

119
Q

____ designs are aimed at finding relationships

A

Exploratory designs

Ex: case-control, cohort, predictive, methodological validity, historical, secondary analysis

120
Q

Logistic regression

Number of IV and DV

A 
IV =  more than 1 
DV = 1
121
Q

ICC interpretation showing “poor to moderate reliability”

A

ICC < 0.75

122
Q 
Case-Control studies. 
Subjects selected based on \_\_\_.
Controls selected from \_\_\_.
Examine if \_\_\_\_.
Works especially well for \_\_.
A

Subjects selected based on whether or not they have the disorder
Control ms should be from same population as cases
Examine if exposure different between cases and controls
Works especially well for very rare conditions
Typically retrospective

123
Q

Aimed at studying determinants of disease, injury, or dysfunction in populations (risk)

A

Epidemiology

124
Q

Recommended that Cronbach’s alpha be between __

A

0.70 to 0.90

125
Q

Correlation coefficients _____ and vary between ___ and ____.

A

Quantify linear relationships

0 and +/- 1.00

126
Q

Multicolinearity data

A

Correlation table

Want to be high and significant,
And others be low nonsignificant

127
Q

Causation statements come from ____

A

Controlled experiments (RCTs)

128
Q

T-test:
IV Level of measurement
DV level of measurement
Question

A

IV : nominal
DV: continuous
Q: difference between means?

129
Q

Method of simplifying and organizing large sets of variables into fewer abstract components

A

Factor analysis

130
Q

Pearson product-moment correlation coefficient applicable when variables are ___ or ___.

A

Interval or ratio (continuous)

131
Q

Extent to which a measurement is free from error

A

Reliability

132
Q

Linear regression, X is __ and ___ is __

A 
X = IV = “predictor” variable
Y = DV = criterion variable

X and Y are correlated

133
Q

Correlation does NOT

A

Assess differences or agreement

ICCs do

134
Q

Nonparametric tests require a ___ sample size compared to parametric

A

Larger

135
Q

A large number of predictors require ___, rule of thumb is __.
Too many predictors or too few subjects, becomes susceptible to ___

A

Very large sample size
10-15 people per predictor in model
Too many predictors or too few subjects - susceptible to model overfit (chance, type 1 error)

136
Q

Cronbach’s alpha can help eliminate ____

A

Items from tests/questionnaires that are not homogeneous to the set or are not contributing unique info

137
Q

Which correlation coefficient?

All ordinal

A

Spearman’s rho

138
Q

Simple linear Regression model based on

A

Line that best fits data

Slope of line equation Y = a + bX
b is slope of line
a is y-intercept
Y= DV and X=IV

The slope (b) is the regression coefficient

139
Q

3 or more independent groups

Parametric and Nonparametric tests

A

Parametric: 1-way analysis of variance (F)
Nonparametric: Kruskal–Wallis analysis of variance by ranks (H or x^2)

EBP2 (1 decks)

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