Introduction to BIostatistics in Epi Flashcards Preview

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Flashcards in Introduction to BIostatistics in Epi Deck (34):
1

3 key attributes of data variables

Magnitude(biger is more, lower is less)
Consistency of scale(or fixed intervals)
-equal, measurable spacing btw units
rational zero
Each can be answered with yes or no repsonse

2

Nominal

Dichotomouse/binary; no order or rank; non ranked categories.... NO magnitude, NO consistency of scale, NO rationonal zero..... examples.... gender, occupationsoal class, party affiliation (ALL dichotomous and non-ranked categories)

3

Ordinal

Ranked Categories; non-equal-distance... YES magnitude, NO consitency of scale, NO rational zero... Rank of canidates in order of preference from worse to best...( all ranked categories)

4

Interval/ Ratio

YES magnitude, YES consitency of scale, NO or YES rational zero (no-interval; yes-ratio) ex... number of living sibilings and age... (all numerical scales with ture units)

5

What type of data is being collected or evaluated?

...

6

What type of comparison/assessment is desired?

Correlation!!!! Correlations test.

7

Correlation

Provides a quantitative measure of the strength and direction of a relationship btw variables.... creates a 45 degree angle.... X goes down, Y goes up....

8

Correlation..... Is the correlation linear? if not significanlty significan then there is NOT linear correlation

ordinal= spearman correlation
nominal= contingency coefficent
interval= pearson correlation

9

Contingency coefficent

if more than .05 it is not significantly significant

10

Time-to event... event-occurrence

survival test... can all be represented by kaplan meier curve

11

Suvival Test

ordinal=cox proportional hazards
nominal= log-rank
interval= kaplan-meier product-limit estimate

12

survial tests....

compares the proprtion of, or time to event occurence btw groups....

13

Outcome prediction/association

Regression

14

Regression (THE WORD PREDICT!!!0

Provide a measure of the relationship btw variables by allowing the prediction about the dependent, or outcome, variable (DV) knowing the value/rank of others independent variables..... able to calculate measerue of associateions

15

Regression tests

Nominal=logistic regression
ordnial= multinominal logistic regression
interval= linear regression

16

Frequencies/ counts/ proportions

HOW MAN GROUPS!

17

is the datat independent or related

Data from the same( paired) ore different groups(independent)?

18

Nominal 2 groups independent data

(Pearsons) Chi-square test

19

nominal greater than 3 independent data

Chi-square test of independence... no cell with expected count of <5.... to predeict 3 more comparisons, one must perform subsequent analysis(post-hoc testing) to determine which groups are different.... Multiple Chi tests NEVER acceptable.... Bonferroni test of Ineqaulity, ver conservative

20

nominal >2 groups with expected cell count of <5

fisher's exact test

21

Nominal 2 groups of paired/related data

McNemar test.... key words... pre vs post... before vs after, basline vs end

22

nominal >3 groups of paired related data

cochran ..... must do bonferroni test of inequality

23

Ordinal 2 groups of independent data

Mann-whitney test

24

Ordinal data >3 groups of independent data

Kruskal wallis test.... compares the mdeian values btw groups.... mujst perform post hoc

25

If related data

before and after... beginning and end... baseline vs end

26

Ordnial data 2 groups of Paired data

Wilcoxon SIgned Rank test

27

Ordinal >3 groups of paired data

Friedman test... do post hoc after

28

Post hoc tests for 3 or more group comparisons

Student-Newman Keul test - comapres all pairwise comparisons possilbe
Dunnett Test- compares agains single.. equal in size
Dunn Test- Compares all possilbe comparisons

29

Interval 2 grousp of independent data

student t test... compares mean values btw groups

30

interval data >3 groups of independent data

ANaysis of Varainace (ANOVA) (1DV)- comapres menas of all groups
Multiple Analysis of Variance (Manova) (>2 DVs) must do post hoc

31

Interval data >3 groups of independent data w cofounders

ANCOVA
MANCOVA

32

Interval 2 groups of data paired

Paired t test

33

interval data >3 groups of paired data

repeated ANOVA
Repeated MANOVA(>2)

34

INterval data>3 paried with cofounders

repeated ANCOVA
Reated MANCOVA