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Exam Block 3 - Fall 2019 > Epi 3: Selecting Statistical Tests > Flashcards

Epi 3: Selecting Statistical Tests Flashcards

1
Q

List 4 different categories that answer question # 2 in selecting correct statistical test.

Q2 = What type of comparison/assessment is desired?

A
  • Correlation - 2 groups
  • Regression - prediction, 3+ groups
  • Survival Comparison - time
  • Group Comparison
    2 vs. 3+ groups;
    independent vs. paired/related
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2
Q

“prediction” indicates which category of statistical tests

A

Regression

3 regression tests = Logistic Regression, Multinominal Logistic Regression, Linear Regression

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3
Q

What does correlation statistical test compare?

A

Quantitative representation of STRENGTH + DIRECTION of a relationship between TWO variables

FIXED value range = [-1 - +1]

\+/- = direction 
value = magnitude of strength
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4
Q

How many Correlation statistical tests? Are any specific to particular data level?

A 
Contingency Coefficient (nominal)
Spearman Correlation (ordinal)
Pearson Correlation (interval)
Kappa Statistic
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5
Q

For Pearson Correlation test, what does a statistically significant value (p < 0.05) and a non-statistically significant value (p > 0.05) indicate?

A

p < 0.05: Linear correlation is present between 2 groups

p > 0.05: NO linear correlation, but may be a non-linear relationship present!!!

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6
Q

Under what circumstances would you run a Pearson Correlation as a “partial correlation”? What level of data would this involve?

A

Partial Correlation = correlation stat. test that controls for confounding variables

Only interval data = Pearson Correlation

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7
Q

Contingency Coefficient

A

Correlation stat. test

Nominal data

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8
Q

Spearman Correlation

A

Correlation statistical test

Ordinal data

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9
Q

Pearson Correlation

A

Correlation stat. test

Interval data

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10
Q

Kappa Statistic

A

A correlation; measures STRENGTH + DIRECTION of agreement between different evaluators;

Compares ability of different evaluators to classify/interpret same data into 1 of many groups.
Ex.- 2 different radiologists interpret/classify the same radiographic image

FIXED value range: [-1 - + 1]

+/- = good agreement/poor agreement

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11
Q

What does a regression measure? What else can be calculated from a regression?

A

Measure of relationship between multiple variables (IV) specific ability to predict outcome variable (DV)

Odds ratio for measure of association + control for confounding variables

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12
Q

How determine the data level of a Regression?

A

= data level of outcome variable (DV) = variable being predicted

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13
Q

What type of data comparison group can calculate Odds Ratio (OR)?

A

regression

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14
Q

Nominal data + regression test =

A

Logistic Regression

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15
Q

Ordinal data + Regression test =

A

Multinominal Logistic Regression

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16
Q

Interval data + Regression test =

A

Linear Regression

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17
Q

Logistic Regression

A

multiple independent variables used to predict outcome/dependent variable (DV)

predicted outcome data level = nominal

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18
Q

Multinominal Logistic Regression

A

multiple independent variables used to predict outcome/dependent variable (DV)

predicted outcome data level = ordinal

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19
Q

Linear Regression

A

multiple independent variables used to predict outcome/dependent variable (DV)

predicted outcome variable data level = interval

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20
Q

List the regression test for each data level.

Nominal, ordinal, and interval data

A

logistic regression
multinominal logistic regression
linear regression

21
Q

For Pearson Correlation test, what does a non-significant value indicate?
(p > 0.05)

A

No LINEAR correlation between groups; however, may be NON-LINEAR correlations present

22
Q

delineate correlation vs. regression types of statistical tests

A

Correlation: relationship between TWO groups; fixed value range

Regression: relationship MULTIPLE IV in predicting an outcome variable (DV);

23
Q

what type of statistical test will only produce values within [-1 - +1]?

A

Correlation

24
Q

Partial Correlation

A

Correlation test ONLY for interval data (Pearson Correlation) that controls for confounding variables

25
Q

List all statistical tests that can be represented by Kaplan-Meier Curve

A

Log-Rank test
Cox-Proportional Hazards test
Kaplan-Meier test

All survival tests

26
Q

“over time” indicates what type statistical comparison

A

survival test

27
Q

Survival test =

A

Compares proportion of events over time, or time-to events, between groups ~ongoing progression~

28
Q

“free from an event” over time

A

survival

29
Q

Log-Rank test

A

survival test + nominal level data

died/didn’t die or developed disease/didn’t develop disease

30
Q

Cox-Proportional test

A

survival test + ORDINAL level data collected

ex. - tumor growth - 0 in., 1-5 in., 5-10 in., etc.

31
Q

Kaplan-Meier TEST

A

survival test + INTERVAL level data

32
Q

List all survival statistical tests for each data level:

A 
nominal = Log-rank 
ordinal = cox-proportional hazards test
interval = kaplan -meier test
33
Q

What is the most commonly utilized type of comparison of statistical data?

A

Group comparisons

34
Q

Which Correlation test can control for confounding factors?

A

Partial Correlation of Pearson Correlation test

35
Q

What kinds of comparisons are made in group comparisons?

A

frequencies
counts
proportions

36
Q

Type of statistical test assess event-occurrence and time-to-event?

A

survival tests

37
Q

What data being compared in Paired/Related Group Comparisons?

A

Comparing data of subjects from the SAME study groups

38
Q

“pre- vs. post-“ “before vs. after” “baseline vs. end” should all indicate what kind of data?

A

Paired or related data - group comparisons

39
Q

What are the required assumptions of interval/ratio data for proper selection of parametric test?

A
  • Normally-distributed
  • Equal Variances
  • Randomly-derived + Independent
40
Q

How do you handle interval/ratio data NOT normally-distributed?

A

1) TRANSFORM data –> Standardized Values (z-score/Log transformation) which might be Normally-distributed
2) Use Non-Parametric tests –> use equivalent stat test of the lower data level
* Always run descriptive statistics and graphs*

41
Q

Null Hypothesis

A

Research perspective that states there will be NO true differences between groups being compared

p value of statistical tests is what is used to determine ACCEPT or REJECT null hypothesis

42
Q

Mann-Whitney test

A

Ordinal data
2-groups
Independent data
compares MEDIANS

43
Q

Wilcoxon Signed Rank test

A

Ordinal data
2-group
Paired/Related data
compares MEDIANS

44
Q

Kruskal-Wallis test

A

Ordinal data
** 3+ groups **
Independent data
compares MEDIANS

** If p value < 0.05, run a POST-HOC test to determine between which groups the difference exists!

45
Q

Friedman test

A

Ordinal data
** 3+ groups **
Paired/Related data
compares MEDIANS

**If p value < 0.05, run a POST-HOC test to determine between which groups the difference exists!

46
Q

Name Post-Hoc tests for ORDINAL data:

A

Student-Newman-Keul
Dunnett
Dunn

Kruskal-Wallis and Friedman

47
Q

What type of tests utilize Post-Hoc tests?

A

Group Comparisons
3+ groups
p value < 0.05

Ordinal data stat tests:

  • Kruskal-Wallis test
  • Friedman test

Interval data stat tests:

  • ANOVA/ANCOVA
  • Repeated Measures ANOVA/ANCOVA
48
Q

(Pearson’s) Chi-Square test

A

Nominal data
2-groups
Independent data
compares PROPORTIONS

Exam Block 3 - Fall 2019 (12 decks)

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