Final Flashcards
1
Q
MCD is a mathematical multiple of ___
A
SEM
2
Q
______ often used to construct and evaluate scales/questionnaires
A
Internal consistency
3
Q
Logistic =
A
Use of categorical variables
DV is categorical
Ex: success vs non-success
4
Q
Which correlation coefficient?
1 ordinal and 1 ratio/interval
A
Spearman’s rho
5
Q
Kappa interpretation
A
Basically same as ICC
Depends on weights used;
Exactly same as ICC when weights squared
< 0.4 poor-fair
- 4-0.6 moderate
- 6-0.8 substantial
- 8-1.0 excellent
6
Q
1-way ANOVA
A
Parametric
3 or more independent groups
1 IV with 3 or more levels
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)
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
9
Q
Discrete (nominal/ordinal) reliability coefficients
A
Percent agreement
Kappa - better
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
11
Q
Logistic regressions primary outcome ____
A
OR (odds ratio)
Null value is 1 (not 0)
12
Q
Which correlation coefficient?
All nominal dichotomy
A
Phi coefficient
13
Q
Linear =
A
Use of continuous variables
DV is continuous
Ex: does age predict BP
14
Q
Which correlation coefficient?
1 nominal dichotomy, 1 ratio/interval
A
Point biserial
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
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
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”
18
Q
Reliability is tied to the concept of
A
Measurement error
19
Q
ICC estimate based on ___ will always be substantially higher than estimate based on ____
A
Average measures always high than single measures
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
21
Q
Paired t-tests
A
Parametric
1 group
1 IV with 2 levels
22
Q
ICC interpretation showing “good reliability”
A
ICC > 0.75
23
Q
ICC Model 1
A
Each subject measured by different set of raters; randomly chosen
Rarely used in clinical research
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
25
Interpretation of correlation coefficients
0. 00-0.25 = little to no relationship
0. 26-0.50 = fair relationship
0. 51-0.75 = moderate to good
0. 76-1.00 = good to excellent
These values are NOT strict cutoff points. Depends on type of research.
26
Most predictors are ___ scale, but can also use ___. But not ____.
Most predictors are continuous scale
Can also be dichotomous or ordinal scale
But NOT multi category nominal (ie race)
27
ANOVA
| Umber of IV and DV
IV : more than 1
| DV: 1
28
Rxx (reliability coefficient) will be bigger when
True variance is larger
29
Nonparametric tests are ___% of parametric tests with regard to power
65-95% as powerful as parametric equivalent
30
Reliability coefficient (rxx) ranges ___ meaning
Range 0-1
0 = no reliability
1 = perfect reliability
31
Multiple linear regression
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
32
Hierarchical Linear Modeling (HLM)
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
33
Standardized Beta Weights
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
34
Correlations only applicable for ___ of scores. Correlations quantify strength of ____ only.
Pairs of scores
| Linear relationships only - based on equation for a straight line.
35
MANOVA
| Number of IV and DV
IV = more than 1
DV = more than 1
MANOVA is for analyzing >1 DV simultaneously
36
Nonparametric stats are based on...
Comparisons of ranks of scores
| Comparisons of counts (yes/no) or “signs” of scores
37
Phi coefficient
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
38
Both ____ and ___ give single indicators of reliability that capture strength of a relationship plus agreement in a single value
ICC and Kappa
39
Problem with correlation coefficient (Pearson’s r)
Assess relationship, not agreement
| Only 2 raters or occasions can be compared
40
___ gives “unstandardized” estimate of reliability (ie untis of measurement)
SEM
41
Cronbach’s alpha represents correlation ____
Among items and correlation of each individual item with the total score
42
Spearman Rank (rho) correlation coefficient (rs)
Nonparametric analog of Pearson’s r
| 1 continuous, 1 ordinal variable OR 2 ordinal variables
43
Analysis of residuals to test assumptions
Plot residuals on ___-axis
Predicted values on ___-axis
Residuals on y-axis
Predicted values on x-axis
Looking for symmetry
44
The amount of change in a variable that must be achieved to reflect a true change/difference
MDC minimal detectable difference/change
45
Point biserial correlation (r pb)
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
46
CV is unit-less, so helpful comparing ____
Variability between 2 distributions on different scales
47
Logistic regression
DV=
Predictors =
DV = dichotomous
| Predictors (IV) = continuous, ordinal or dichotomous
48
We use __ to predict ___ In linear regression
X (IV) to predict Y (DV)
49
3 types of stepwise procedures
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
50
___ is stability of repeated measures over time. Is basically the same as test-retest reliability
Response stability
51
Kappa can be used on __ data
Nominal and ordinal
52
Adjusted R^2
Chance corrected R^2
Adjusted down for having more predictor variables
Accuracy of prediction
53
The % of variance in y that is explained (or accounted for) by x
Coefficient of determination
54
Multicolinearity
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
55
Non-parametric:
IV Level of measurement
DV level of measurement
Question
IV: nominal
DV: ordinal
Q: ranks different?
56
Regression line of best fit
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
_____ uses relationships (correlation) as a basis for prediction
Regression analysis
58
Cautions with interpretations of correlation
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
Bias =
Mean difference
60
Which correlation coefficient?
| All data ratio/interval
Pearson r
61
LOA
Limits of agreements
| Range include ~95% of differences
62
Case-control and cohort studies are of ____ design, and intend to study ___. Generally IV and DV are ___ variables
Exploratory design
Intended to study risk factors (assoc between disease and exposure)
Both IV and DV dichotomous
63
Continuous (interval/ratio) reliability coefficients
```
Pearson correlation (r)
Intraclass correlation coefficient (ICC)- better
```
64
Outliers effect on regression line
Outliers/deviant scores have large effect on regression line
65
Which correlation coefficient?
| 1 nominal dichotomy, 1 ordinal
Rank biserial
66
MANOVA: ___ DV, ___ groups
2 or more DV
3 or more groups
MANOVA combines multiple DVs into 1 “combo DV”
67
Cohen’s kappa coefficients used for _____
Categorical scale scores
68
Weighted kappa best for ____. Weights can be ___ and ____.
| Can choose to make “penalty” ____ for ___
Best for ordinal data
Weights can be arbitrary, symmetric or asymmetric
Penalty worse for larger disagreements
69
Interpreting relative risk/odds ratios
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
Epidemiology generally uses ___ designs with ___ variables
```
Observational design
Dichotomous variables (disease or no disease/ exposed or unexposed)
```
71
Significance of coefficient: p-value and CI
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
2 related scores
| Parametric and Nonparametric tests
Parametric: paired t-test
Nonparametric: Wilcoxon signed-ranks test (T)
Sign test
73
Percent agreement is simply ____. Calculate by...
How often raters agree
| Divide number of agreements by total of all possible agreements
74
Correlation
| Number of IV and DV
```
IV = 1
DV = 1
```
75
Rank biserial correlation (r rb)
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
ICC interpretation p-value tests whether
Point estimate is statistically different from 0
77
Stated in terms of variance, reliability =
True score reliability
_____________________________
(True score variability + error variability)
78
ICC model 3
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
Most common correlation coefficient
Pearson product-moment correlation coefficient (r)
80
ICC give ______ estimate of reliability (ie no units) and often reported in conjunction with
“Standardized”
| SEM
81
Relative Risk
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
The first number in ICC type is __ the second number is ___
Model
| Form
83
ANOVA:
IV Level of measurement
DV level of measurement
Question
IV: nominal
DV: continuous
Q: difference between means?
84
Linear regression
| Number of IV and DV
```
IV = 1
DV = 1
```
85
Correlation coefficient (R) for regression
Rough indicator of goodness of good fit for regression line
Same as correlation coefficient (r)
Accuracy of prediction
86
Visual modeling of both direct and indirect relationships.
| Can analyze both direct and indirect relationships between....
Path analysis
Can analyze both direct and indirect relationships between
1 or more exogenous variables (IV)
1 or more endogenous variables (DV)
87
ANOVA: ____ DV, ____ groups
1 DV, 3 or more groups
88
ICC forms
2nd number in parentheses represents number of observations used to obtain reliability estimate
89
SEM (std error if measurement) is _____ measure of reliability.
It is ______
Absolute
Standard deviation of the distribution of theoretical multiple measurements
It is mathematical multiple of ICC
90
Odds ratio
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
Regression:
IV Level of measurement
DV level of measurement
Question
IV: continuous
DV: continuous
Q: strength of prediction?
92
Observed score is
True score +/- error
93
ICC interpretation that is “best for clinical measurements”
ICC > 0.90
94
T-tests: number of IV and DV
```
IV = 1
DV = 1
```
95
Correlation coefficients:
Sign indicates ____.
(+) (-)
____ means higher coefficient
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
Reliability for categorical scales based on ______. Agreements are ___ and disagreements are ___.
Frequency table
Agreements on diagonal
Disagreements are all others
97
ICC model 2
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
Cohort studies. Subjects selected based on ____. Usually ___, but can be ____. Examine ___. Doesn’t work well for ___.
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
Nonparametric tests are unable to be performed on...
Complex designs like 2x3
100
Stepwise procedures in multiple regression models
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
ICC (intraclass correlation coefficients) used for
Continuous scale scores
| But can be used for original data if intervals “assumed” to be equivalent (like a pain scale)
102
Pro and con of MANOVA
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
Regression coefficient (B)
Value/slope in linear equation
Rate of change in Y for each unit change of X
Accuracy of prediction
104
Ratio of std deviation to mean, expressed as a percentage
CV coefficient of variation
105
Covariance means
As one changes, the other also changes
106
ICC Form 1
Only 1 observation per subject per rater (or rating)
107
Problem with percent agreement
Does not account for agreement due to chance
| Tends to overestimate reliability
108
Multiple linear regression
| Number of IV And DV
```
IV = more than 1
DV = 1
```
109
2 independent groups
| Parametric and Nonparametric tests
Parametric: unpaired t-test
Nonparametric: Mann-Whitney U test
110
Correlation:
IV Level of measurement
DV level of measurement
Question
IV: continuous
DV: continuous
Q: strength of association?
111
Unpaired t-test
Parametric
2 independent groups
1 IV with 2 levels
112
Mann-Whitney U test
Dependent variable Ordinal
Can not assume normal distribution
2 independent groups
1 IV with 2 levels
113
3 or more related scores
| Parametric and Nonparametric tests
Parametric: 1-way repeated measures analysis of variance (F)
Nonparametric: Friedman 2-way analysis of variance by ranks (x^2r)
114
Kappa coefficient is proportion of agreement ____
Between raters after chance agreement has been removed
115
Receiver operating characteristics (ROC) used to
Find cut off scores (dichotomous data)
116
__ types of ICC depending on
```
6 ICC types
Depends on:
Purpose of study
Design of study
Type of measurements
```
117
Odds ratio and case control studies are selected based on ____, so cant determine ___
Selected based on whether they have disease or not,
| Can’t determine rate of incidence
118
Wilcoxon sign-ranks test
Dependent variable Ordinal
Can not assume normal distribution
1 group
1 IV with 2 levels
119
____ designs are aimed at finding relationships
Exploratory designs
Ex: case-control, cohort, predictive, methodological validity, historical, secondary analysis
120
Logistic regression
| Number of IV and DV
```
IV = more than 1
DV = 1
```
121
ICC interpretation showing “poor to moderate reliability”
ICC < 0.75
122
```
Case-Control studies.
Subjects selected based on ___.
Controls selected from ___.
Examine if ____.
Works especially well for __.
```
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
Aimed at studying determinants of disease, injury, or dysfunction in populations (risk)
Epidemiology
124
Recommended that Cronbach’s alpha be between __
0.70 to 0.90
125
Correlation coefficients _____ and vary between ___ and ____.
Quantify linear relationships
| 0 and +/- 1.00
126
Multicolinearity data
Correlation table
Want to be high and significant,
And others be low nonsignificant
127
Causation statements come from ____
Controlled experiments (RCTs)
128
T-test:
IV Level of measurement
DV level of measurement
Question
IV : nominal
DV: continuous
Q: difference between means?
129
Method of simplifying and organizing large sets of variables into fewer abstract components
Factor analysis
130
Pearson product-moment correlation coefficient applicable when variables are ___ or ___.
Interval or ratio (continuous)
131
Extent to which a measurement is free from error
Reliability
132
Linear regression, X is __ and ___ is __
```
X = IV = “predictor” variable
Y = DV = criterion variable
```
X and Y are correlated
133
Correlation does NOT
Assess differences or agreement
| ICCs do
134
Nonparametric tests require a ___ sample size compared to parametric
Larger
135
A large number of predictors require ___, rule of thumb is __.
Too many predictors or too few subjects, becomes susceptible to ___
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
Cronbach’s alpha can help eliminate ____
Items from tests/questionnaires that are not homogeneous to the set or are not contributing unique info
137
Which correlation coefficient?
| All ordinal
Spearman’s rho
138
Simple linear Regression model based on
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
3 or more independent groups
| Parametric and Nonparametric tests
Parametric: 1-way analysis of variance (F)
Nonparametric: Kruskal–Wallis analysis of variance by ranks (H or x^2)
