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Epidemiology 2018 > Statistical tests (intro to biostats lecture) > Flashcards

Statistical tests (intro to biostats lecture) Flashcards

1
Q

Student t-test

A

Interval

2 groups

Independent

Compares the means of all groups (along with intra and inter-group variations) against a dependent variable

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2
Q

(Pearson’s) Chi square (include its 2 assumptions)

A

Nominal

2 Groups

Independent

Compares group proportions and if they are different from that expected by chance

(usual chi-square data distribution and no cell count less than 5)

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3
Q

Fisher’s exact test

A

Nominal

2 groups OR more than 2 groups

Independent

Groups have an EXPECTED cell count of <5

(Bonferroni to adjust the p value for the # of groups being compared IF there are more than 2 groups being compared)

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4
Q

Chi square test of independence

A

Nominal

More than 2 Groups

Independent

(Bonferroni to adjust the p value for the # of groups being compared)

(usual chi-square data distribution and no cell count less than 5)

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5
Q

Bonferroni test of inequality (include the 3 tests run prior to the use of the bonferroni test)

A

Nominal

More than 2 groups

Independent OR related data

adjusts the p value for the # of groups being compared

(Chi squared of independence, Fisher’s exact, and Cochran are all tests that require the bonferroni as a “post hoc” test if they yield statistically significant findings [p value < 0.05])

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6
Q

McNemar test

A

Nominal

2 groups

Related

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7
Q

Cochran Q test

A

Nominal

More than 2 groups

Related data

Same principle/assumptions as chi squared, but it factors in related/paired data

(Bonferroni to adjust the p value for the # of groups being compared)

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8
Q

Mann-Whitney Rank Sum

A

Ordinal

2 groups

Independent data

Compares the median values between groups

(also used for interval data that does not meet parametric requirements)

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9
Q

Wilcoxson Signed Ranke

A

Ordinal

2 groups

Related data

Compares the median values between groups

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10
Q

Kruskal-Wallis Test (include what it needs if its value is statistically significant)

A

Ordinal

more than 2 groups

Independent data

Compares the median values between groups

(Student-Newman-Keul, Dunnett, or Dunn post hoc tests must be run to determine where there differences are when there are more than 2 groups)

(also used for interval data that does not meet parametric requirements)

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11
Q

Friedman Test (include what it needs if its value is statistically significant)

A

Ordinal

More than 2 groups

Related data

(Student-Newman-Keul, Dunnett, or Dunn post hoc tests must be run to determine where there differences are when there are more than 2 groups)

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12
Q

Levene test of equal variances

A

determines how “normally distributed” and the level of “equal variances” that are occurring in the data set

“it asks if the groups are equal”

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13
Q

paired t test

A

Interval

2 groups

Related data

Compares the mean values between groups that are related

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14
Q

ANOVA (include what it may need and why)

A

Interval

More than 2 groups

Independent data

Compares the means of all groups (along with intra and inter-group variations) against a dependent variable

(if this group comparison yields a statistically significant value, then a post hoc test must be conducted)(Bonferroni, Tukey, Scheffe, Dunn, Dunnet, Student-Newman-Keul)

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15
Q

ANCOVA (include what it may need and why)

A

Interval

More than 2 groups

Independent data

Confounders present

Compares the means of all groups (along with intra and inter-group variations) against a dependent variable while also controlling for the co-variance of confounders

(if this group comparison yields a statistically significant value, then a post hoc test must be conducted)(Bonferroni, Tukey, Scheffe, Dunn, Dunnet, Student-Newman-Keul)

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16
Q

Repeated measures ANOVA

A

Interval

More than 2 groups

Related data

Compares the means of all groups (along with intra and inter-group variations) of RELATED data against a dependent variable

(if this group comparison yields a statistically significant value, then a post hoc test must be conducted)(Bonferroni, Tukey, Scheffe, Dunn, Dunnet, Student-Newman-Keul)

17
Q

Repeated measures ANCOVA

A

Interval

More than 2 groups

Related data

Confounders present

Compares the means of all groups (along with intra and inter-group variations) against a dependent variable while also controlling for the co-variance of confounders

(if this group comparison yields a statistically significant value, then a post hoc test must be conducted)(Bonferroni, Tukey, Scheffe, Dunn, Dunnet, Student-Newman-Keul)

18
Q

Cox-Proportional Hazards test

A

Ordinal

Proportion with event (survival)

Compares the number of ordinal data events over time

19
Q

Logistic regression

A

Nominal

Prediction or Association

(Predicts the outcome [dependent variable])

(you are able to calculate an OR for a measure of association)

20
Q

Linear Regression

A

Interval

Prediction or Association

(Predicts the outcome [dependent variable])

(you are able to calculate an OR for a measure of association)

21
Q

Multinominal Logistic Regression

A

Ordinal

Prediction or Association

(Predicts the outcome [dependent variable])

(you are able to calculate an OR for a measure of association)

22
Q

Kaplan-Meier test

A

Interval

Proportion with event (survival)

Time itself is being evaluated

23
Q

What can be represented by a kaplan-meier curve?

A

all survival tests

Log-Rank, Cox-Proportional hazards, and kaplan-meier test

24
Q

Contingency Coefficient

A

Nominal

Correlation is desired

(partial correlation if you need to control for confounding)

25
Q

Pearson Correlation

A

Interval

Correlation is desired

(partial correlation if you need to control for confounding)

A p value >0.05 with this test just means that there is no “linear” correlation, and there may still be non-linear correlations present

26
Q

Log Rank Test

A

Nominal data

Proportion of events (survival)

Compare that proportion of nominal data value over time

27
Q

Spearman correlation

A

ordinal

Correlation is desired

(partial correlation if you need to control for confounding)

28
Q

Student-Newman-Keul test

A

Student-Newman-Keul test: compares all pairwise comparisons possible and all groups MUST be equal in size

29
Q

Dunnett test

A

Dunnett test: Compares all pairwise comparisons against a SINGLE CONTROL and all groups must be equal in size

30
Q

Tukey test

A

Tukey test: compares all pairwise comparisons possible and all groups MUST be equal in size

Slightly more conservative than the Student-Newman-Keul

Scheffe test is less affected by

31
Q

Dunn test

A

Dunn test: compares all pairwise comparisons possible and is useful when all groups are NOT of equal size

32
Q

Scheffe test

A

Scheffe test: compares all pairwise comparisons possible and all groups MUST be equal in size

Scheffe test is less affected by violations in normality and homogeneity of variances - most conservative

Epidemiology 2018 (15 decks)

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