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Epidemiology > Lecture 34-37: The Rest Of Biostats > Flashcards

Lecture 34-37: The Rest Of Biostats Flashcards

1
Q

Nominal –> 2 Groups –> Independent

A

(Pearson’s) Chi-square test (X(squared))
Or
Fischer’s Exact

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2
Q

Nominal –> 2 Groups –> Related

A

McNemar

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3
Q

Nominal –> 3 or More Groups –> Independent

A

Chi-square test of Independence
Or
Fischer’s Exact

(2 of 3 Bonferonni’s Test of Inequality)

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4
Q

Nominal –> 3 or More Groups –> Related

A

Cochran

One of Three Bonferronni Tests of Inferiority

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5
Q

Nominal –> Proportion of Events (Survival)

A

Log-Rank

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6
Q

Nominal –> Measure of Correlation –>

A

Contingency Coefficient

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7
Q

Nominal –> Prediction or Association

A

Logistic Regression

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8
Q

Ordinal –> 2 Groups –> Related

A

Wilcoxon-Signed-Rank

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9
Q

Ordinal –> 2 Groups –> Independent

A

Mann Whitney

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10
Q

Ordinal –> 3 or more groups –> Independent

A 
Kruskal Wallis
-->
Student-Newman-Keul
Dunnett 
Dunn
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11
Q

Ordinal –> 3 Or More Groups –> Related

A

Friedman

Post-Hoc:
Student-Newman-Keul
Dunnett
Dunn

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12
Q

Ordinal –> Correlations

A

Spearman Correlation

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13
Q

Ordinal –> Associations or Predictors

A

Multinomial Logistic Regression

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14
Q

Ordinal –> Survival

A

Cox Proportional Hazard

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15
Q

Interval –> 2 Groups –> Independent

A

Student t

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16
Q

Interval –> 2 Groups –> Related

A

Paired t

17
Q

Interval –> 3 Or More Groups –> Independent

A

ANOVA or MANOVA

Leads to Confounders Present

Leads to ANCOVA or MANCOVA

18
Q

Interval –> 3 or More Groups –> Related

A

Repeated Measures ANOVA
Or
Repeated Measures MANCOVA

If Confounder Present:

Repeated Measures ANCOVA
Or
Repeated Measures MACNOVA

19
Q

Interval –> Survival

A

Kaplan-Meier

20
Q

Interval –> Correlation

A

Pearson Correlation

21
Q

Interval –> Prediction or Association

A

Linear Regression

22
Q

Name the 6 Post-Hoc Tests

A 
Bonferonni
Tukey
Scheffe
Dunn
Dunnett
Student-Newman-Keul
23
Q

When Determining the Correct Statistical Test (and after deciding what data type it is), what is the next question to ask to determine which test to use?

A

What Type of Comparison/Assessment is desired?

24
Q

Define Correlations

A
  • Correlation (r)
  • Provides a QUANTITATIVE measure of the STRENGTH & DIRECTION of a relationship between variables
  • -VALUES RANGE FROM -1.0 TO +1.0
  • Partial Correlation
  • A correlation that controls for confounding variables
25
Q

What are the three types of correlation tests?

A
  • Nominal Correlation test = CONTINGENCY COEFFICIENT
  • Ordinal Correlation test = SPEARMAN CORRELATION
  • Interval Correlation test = PEARSON CORRELATION

– p>0.05 for a Pearson Correlation just means there is no LINEAR correlation; there may still be NON-LINEAR correlations present!

  • ALL CORRELATIONS CAN BE RUNS AS A “PARTIAL CORRELATION” TO CONTROL FOR CONFOUNDING
26
Q

Describe Survival Tests

A
  • Compares the proportion of, or time-to, event occurrences between groups
  • Commonly represented by a KAPLAN-MEIER CURVE
27
Q

List the types of survival Tests

A

Event-Occurrence / Time-to-Event –> SURVIVAL TEST
– Nominal Survival test = LOG-RANK TEST
– Ordinal Survival test = COX-PROPORTIONAL HAZARDS TEST
– Interval Survival test = KAPLAN-MEIER TEST

-ALL CAN BE REPRESENTED BY A KAPLAN-MEIER CURVE

28
Q

Define A Regression Test

A
  • Provide a measure of the relationship between variables by allowing the prediction about the dependent, or outcome, variable (DV) knowing the value/category of independent variables (IV’s)
  • ALSO ABLE TO CALCULATE ODDS RATIO FOR A MEASURE OF ASSOCIATION
29
Q

List the Possible Regression Tests

A

Outcome Prediction/Association (OR) –> REGRESSION
– Nominal Regression test = LOGISTIC REGRESSION
– Ordinal Regression test = MULTINOMIAL LOGISTIC REGRESSION
– Interval Regression test = LINEAR REGRESSION

30
Q

Once again, what are the 4 big questions to ask regarding choosing the correct statistical test

A
  1. What DATA LEVEL is being recorded?
    a. Does the data have MAGNITUDE? (yes/no)
    b. Does the data have a fixed, measureable INTERVAL along the entire scale? (yes/no)
  2. What TYPE OF COMPARISON/ASSESSMENT is desired?
    – Frequencies/Counts/Proportions*
  3. *HOW MANY GROUPS are being compared?
    - 2 or 3 or more groups
  4. *Is the data INDEPENDENT or RELATED (PAIRED)?
    - Data from the same (paired) or different groups (independent)
31
Q

With Three or More Groups of Independent Nominal Data, Describe the test used.

A
  • Chi-square test of Independence (X2)
  • Both this test and the Pearson Chi-Square test for 2 Groups compares group proportions and if they are different from that expected by chance
  • Assumptions:
  • Usual chi-square (binomial) distribution for nominal-type data
  • No cell with Expected count of <5
  • For ≥2 Groups with EXPECTED cell count of <5:
  • Use Fisher’s Exact test
  • For statistically significant findings (p<0.05) in 3 or more comparisons, one Must perform subsequent analysis (POST-HOC TESTING) to determine which groups are different:
  • Multiple X2 tests are NEVER acceptable
    • Risk of Type 1 error increases with each additional test! (almost guaranteed after 4-5 tests)
  • BONFERRONI TEST OF INEQUALITY (BONFERRONI CORRECTION)
    • Adjusts the p value for # of comparisons being made
    • Very conservative
32
Q

Describe Paired/Related Nominal Data

A
  • 2 Groups of Paired/Related Data*
  • MCNEMAR test
  • ≥3 Groups of Paired/Related Data*
  • COCHRAN
    • Same principle and assumptions as X2 yet mathematically factors in concept of paired, or related, data
    • BONFERRONI TEST OF INEQUALITY (BONFERRONI CORRECTION): Adjusts the p value for # of comparisons being made. Very conservative.
  • KEY WORDS FOR “PAIRED” or “RELATED” DATA:
    “Pre- vs. Post-”, “Before vs. After”, “Baseline vs. End”, etc…
33
Q

Describe Independent Ordinal Data

A
  • 2 Groups of Independent Data
  • MANN-WHITNEY TEST
  • ≥3 Groups of Independent Data
  • KRUSKAL-WALLIS TEST
    • Both tests compares the median values between groups. Both also used for Interval data not meeting parametric requirements
    • If 3+ group comparison significant, must perform a POST-HOC TEST to determine where difference(s) is(are)…
34
Q

Describe Paired/Related Ordinal Data

A
  • 2 Groups of Paired/Related Data*
  • WILCOXON SIGNED RANK TEST
  • ≥3 Groups of Paired/Related Data*
  • FRIEDMAN TEST
    • Both tests compares the median values between groups. Each also effective for non-normally distributed Interval data or don’t meet all parametric requirements
    • If 3+ group comparison significant, must perform a POST-HOC test to determine where differences are…
  • KEY WORDS FOR “PAIRED” or “RELATED” DATA:
    “Pre- vs. Post-”, “Before vs. After”, “Baseline vs. End”, etc…
35
Q

Describe the Post-Hoc Tests for Ordinal Data involving 3 or more groups

A
  • STUDENT-NEWMAN-KEUL
  • Compares all pairwise comparisons possible
  • All groups must be equal in size
  • DUNNETT test
  • Compares all pairwise comparisons against a Single Control
  • All groups must be equal in size
  • DUNN test
  • Compares all pairwise comparisons possible
  • Useful when all groups are Not of equal size
36
Q

Incomplete

A

Resume on Slide 94

Epidemiology (17 decks)

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