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(J) Epidemiology Test 3 > Lecture 24-32 - Intro To Biostats In Epidemiology > Flashcards

Lecture 24-32 - Intro To Biostats In Epidemiology Flashcards

1
Q

What are the 3 primary levels of variable?

L24 S5

A
  • nominal
  • ordinal
  • interval/ratio
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2
Q

What are the 3 key attributes of variables?

L24 S5

A
  • order/magnitude
  • consistency of scale
  • rational absolute zero
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3
Q

What is nominal data?
What are its characteristics?

L24 S6

A
  • consists of labeled variables without quantitative characteristics
  • can be dichotomous or binary in nature
  • no order/magnitude
  • no consistency of scale
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4
Q

What is ordinal data?

What are its attributes?

A

-contains rank-able categories that are not evenly spaced

  • yes order/magnitude
  • no consistency of scale
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5
Q

What is interval data?
What are its attributes?

L24 S8

A
  • rankable categories that are evenly spaced
  • arbitrary 0 value that does not mean absence of measured value
  • yes order/magnitude
  • yes consistency of scale
  • no rational absolute zero
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6
Q

What is ratio data?
What are its attributes?

L24 S8

A
  • rankable categories that are evenly spaced
  • absolute 0 value that indicates absence of measured value
  • yes order/magnitude
  • yes consistency of scale
  • yes rational absolute zero
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7
Q

What is the order of specificity of data types?
In which direction(s) can you convert data types?

L25 S12

A

Nominal < Ordinal < Interval < Ratio

Data can only be converted down in specificity, not up

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8
Q

What percentage of data is within one, two, and three standard deviations of the mean in a normally distributed data set?

L26 S23

A 
One deviation (-1 to +1):
-68%
Two deviations (-2 to +2):
-95%
Three deviations (-3 to +3):
-99.7%
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9
Q

What is name given to the types of tests that are used on normally distributed data sets?

L26 S23

A
  • parametric test
  • or-
  • interval test
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10
Q

What determines if a data set is skewed?
What makes a data set positively skewed?
Negatively skewed?

L26 S24-25

A

-mean and median differ from one another

Positively skewed:

  • mean is higher than median
  • tail goes to the right/positive direction

Negatively skewed:

  • mean is lower than median
  • tail goes to the left/negative direction
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11
Q

What does skewness represent?

L26 S35

A

-the measure of asymmetry of a distribution

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12
Q

What is kurtosis?
What do a negative, zero, and positive kurtosis represent?

L26 S37

A

-measure of the extent to which data clusters around the mean

Negative kurtosis:
-less cluster

Zero kurtosis:
-normal distribution

Positive kurtosis:
-more cluster

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13
Q

Calculating the mean on nominal and ordinal data can be done but it can’t be interpreted, why is this?

L26 S40-43

A

The numbers assigned to data is arbitrary and can be changed. (There is no consistency of scale and there are no units)

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14
Q

What is the name of the test that can be used to assess for equalness of variance between groups?

L26 S44

A

-Levene’s test

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15
Q

How do you assess data sets that are not evenly distributed?

L26 S45

A
  • use tests that do not require normal distribution (non-parametric tests)
  • transform the data to a standard value (z-score or log transformation) to make it normally distributed
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16
Q

What are type 1 and type 2 errors?

L26 S47-49

A

Type 1 error:

  • when the null hypothesis is true and should have been accepted, but wasn’t
  • there is no true difference between groups but it was said that there is

Type 2 error:

  • when the null hypothesis is false and should have been rejected but wasn’t
  • there is a true difference between groups but it was said that their isn’t
17
Q

What factors should be looked at to determine if a study’s results are statistically significant?

L27 S50

A
  • power: the ability of a test to detect if there are true differences between groups
  • sample size: the greater the sample size the greater the studies ability to detect if there is a difference between groups
  • p value
  • confidence interval
19
Q

What are the typical accepted type 1 and type 2 error rates?

L27 S51

A

Type 1:
-5%

Type 2:
-20%

20
Q

What are some ways that p value can be interpreted as?

L27 S56

A
  • probability of making a type 1 error if the null hypothesis is rejected
  • probability of erroneously claiming a difference between groups when one does not really exist
  • probability of obtaining group differences as great or greater if the groups were actually the same or equal
  • probability of obtaining test statistic as high/higher if the groups were actually the same/equal
21
Q

Where is it desired to see that there is no statistical difference between groups?

L27

A
  • baseline data

- Levene’s test

22
Q

What does power mean with respects to statistical significance?

L27 S50

A

-the ability of a study to determine if there is a true difference between groups

1 - (type 2 error rate)

23
Q

What is a confidence interval?

L28 S63

A

-percentage of confidence that statistically includes the real relationship being compared

24
Q

If the confidence interval of a ratio contains the number ____________ it is statistically insignificant.

If the confidence interval of an absolute difference contains the number __________ it is statistically insignificant.

L28 S65-66

A

1; 0

25
Q

What factors should be included in the interpretation of a confidence interval?

L29 S65

A
  • level of confidence
  • interpretation of range
  • statement of statistical significance
  • statement of the groups being compared
26
Q

What questions should be asked when selecting a statistical test?

L29 S91

A
  • what is the level of data being collected (nominal/ordinal/interval)?
  • what type of comparison/assessment is desired (frequencies/counts/proportion)
  • how many groups are being compared (2 or >3) ?
  • is the data independent or related (from the same person or not)?
27
Q

What is a correlation test?

What are the correlation tests for each data level?

L29 S75

A

-provides a quantitative measure of the strength and direction of relationship between variable

Nominal:
-contingency coefficient

Ordinal:
-Spearman correlation

Interval:
-Pearson correlation

28
Q

What is a survival test?

What are the survival tests for each level of data?

L30 S81-83

A
  • compares proportion of event occurrence over time between groups
  • “changes over time”
  • “time to event”
  • can be graphed as a Kaplan-Meier curve (regardless of data level)

Nominal:
-Log-Rank test

Ordinal:
-Cox-Proportional Hazards test

Interval:
-Kaplan-Meier test

29
Q

What is a regression test?

What are the regression tests for each level of data?

L30 S84-86

A
  • measure of relationship between variables to predict an outcome
  • able to calculate an odds ratio
  • “predict”

Nominal:
-logistic regression

Ordinal:
-multinomial logistic regression

Interval:
-linear regression

30
Q

What test is used to evaluate NOMINAL data of 2 INDEPENDENT groups and >3 INDEPENDENT groups?

L31 S93

A

2 groups:
-Pearson’s Chi-square test

> 3 groups:
-chi-square test of independence

When there are less than 5 observations of an occurrence, Fisher’s exact test is used instead of the two listed above.

31
Q

What must be done in groups of NOMINAL data of more than 3 when there is found to be a statistically significant difference between groups?

L31 S95

A

Post-hoc testing must be done to determine between which groups the statistically significant difference occurs.

ex. Bonferroni test of inequality (Bonferroni correction)

32
Q

What test is used to evaluate NOMINAL data of 2 RELATED groups and >3 RELATED groups?

What words should indicate that data is related?

L31 S96

A

2 groups:
-McNemar test

> 3:
-Cochran

Indicators of related data:

  • pre- vs. post-
  • before vs. after
  • baseline vs. end
33
Q

What test is used to evaluate ORDINAL data of 2 INDEPENDENT groups and >3 INDEPENDENT groups?

L32 S97

A

2 groups:
-Mann-Whitney test

> 3 groups:
-Kruskal-Wallis test

34
Q

What must be done in groups of ORDINAL data of more than 3 when there is found to be a statistically significant difference between groups?

L32 S99

A

Post-hoc testing must be done to determine between which groups the statistically significant difference occurs.

Student-Newman-Keul test:

  • compares all comparisons possible
  • groups must be equal in size

Dunnett test:

  • compares all comparisons against a single control
  • groups must be the same size

Dunn test:

  • compares all comparisons possible
  • can be used when groups are not equal in size
35
Q

What test is used to evaluate ORDINAL data of 2 RELATED groups and >3 RELATED groups?

What words should indicate that data is related?

L32 S98

A

2 groups:
-Wilcoxon Signed Rank test

> 3:
-Freidman test

Indicators of related data:

  • pre- vs. post-
  • before vs. after
  • baseline vs. end
36
Q

What test is used to evaluate INTERVAL data of 2 INDEPENDENT groups and >3 INDEPENDENT groups?

L32 S100

A

2 groups:
-Student t-test

> 3 groups:

  • Analysis of variance (ANOVA)
  • Analysis of Co-Variance (ANCOVA) (used to control for confounding)
37
Q

What test is used to evaluate INTERVAL data of 2 RELATED groups and >3 RELATED groups?

What words should indicate that data is related?

L32 S102

A

2 groups:
-Paired t-test

> 3:

  • Repeated Measures of ANOVA
  • Repeated Measures of ANCOVA (used to control for confounding)

Indicators of related data:

  • pre- vs. post-
  • before vs. after
  • baseline vs. end
38
Q

What must be done in groups of INTERVAL data of more than 3 when there is found to be a statistically significant difference between groups?

L32 S104-105

A

Post-hoc testing must be done to determine between which groups the statistically significant difference occurs.

Student-Newman-Keul test -or- Tukey test -or- Scheffe test:

  • compares all comparisons possible
  • groups must be equal in size

Dunnett test:

  • compares all comparisons against a single control
  • groups must be the same size

Dunn test:

  • compares all comparisons possible
  • can be used when groups are not equal in size

Bonferoni Correction:
-adjusts p value for # of comparisons (very conservative)

39
Q

What does a Kappa statistic show?

L32 S106

A
  • correlation test showing the level of consistency or agreement between different evaluators
  • ranges from +1 to -1
  • value of “+1” shows observers decision perfectly agree with each other
  • value of “0” shows there is no relationship between observers decisions
  • value of “-1” shows observers decisions perfectly oppose each other

(J) Epidemiology Test 3 (2 decks)

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