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Epidemiology Exam 3 > Biostats > Flashcards

Biostats Flashcards

1
Q

What are the three groupings for data variables?

A

Order/Magnitude

Consistency of scale/equal distances

Rational Absolute Zero

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2
Q

____ determines the appropriate statistical test

A

Data Type

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3
Q

What does order or magnitude mean?

A

Can you quantify the difference?

Is something bigger or smaller than something else?

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4
Q

What does consistency of scale or equal distances mean?

A

Does the value have units

Can you show the difference between values consistently

Can you calculate the range

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5
Q

If you see a dichotomous data set, automatically think its what type of data?

A

Nominal

Ex: Smoking/Non-Smoking
2 Age groups

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6
Q

Give an example where nominal data can have multiple categories

A

Car Brands: Ford, Dodge, Honda etc

Ice Cream Flavors: Chocolate, Strawberry, Cookies n’ Cream

In healthcare, a number association with a blood test or outcome is still nominal since there is no relationship of magnitude between the test and the number associated with it

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7
Q

What are the attributes for nominal data?

A

No order or magnitude (no quantitative association)

No consistency of scale or equal distances

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8
Q

Explain Ordinal data and include the two elements

A

Order, rankable data

There is order or magnitude but NO consistency of scale or equal distances. No way to quantitatively separate pain scale elements

Ex: Pain Scale, Income Brackets, SES

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9
Q

Explain Interval data (2) with include the two elements

A

Interval data can have negatives
Ratio has an absolute zero (physiological parameters)

Does have order/magnitude and does have consistency of scale

Ex: A1C, Height, LDL, Speed

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10
Q

____ and ____ data are discrete while ____ data is continious

A

Nominal and Ordinal

Interval/ratio

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11
Q

What are the two measures of central tendency to identify spread or dispersion?

A

Variance

SD

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12
Q

What type of test is used for normally-distributed data?

A

Parametric tests

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13
Q

Describe a positively skewed data distribution

A

Asymmetrically distribution with one tail longer, right sided.

Mean > Median

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14
Q

Describe a negatively skewed data distribution

A

Asymmetrically distribution with one tail longer, left sided.

Mean < Median

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15
Q

Outliers (do/dont) influence mode

A

don’t

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16
Q

Outliers (do/dont) influence mean and median

A

do

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17
Q

If you have skewed data, you must rule out what kind of statistical test?

A

Interval data

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18
Q

What are the values from 1 SD, 2SD and 3SD?

A

68%

95%

99.7%

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19
Q

Kurtosis

A

Measure of the extent to which observations cluster around the mean

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20
Q

Positive Kurtosis

A

Narrow, tight bell curve with more clustering of mean

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21
Q

Negative Kurtosis

A

Fat bell curve with less clustering of mean

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22
Q

What are the 4 ways to determine if a data set is normally distributed?

A

Levene’s Test
Skewiness
Draw and Analyze a graph
Analyze Mean and Median

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23
Q

What are ways to deal with non-normally distributed data

A

Convert it into a standardized value: Z-Score “log” transferred the data
Drop the stat test to a ordinal test (non-parametric test)

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24
Q

Skewiness

A

Measure of the asymmetry of a distribution

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25
Q

What descriptive statistical elements are useful for nominal data? ordinal data? interval data?

A

Nominal: Mode
Ordinal: Mode and Median
Interval: Mode, Median and Mean

26
Q

Type I Error

A

Also known as Alpha

Rejecting the null hypothesis when it is true (should have accepted it)

27
Q

Type II Error

A

Also known as Beta

Accepting the null hypothesis when it is false (shouldn’t have accepted it)

28
Q

What is power?

A

The statistical ability of a study to detect a true difference, IF one truly exists between group-comparisons, and therefore the level of accuracy in correctly accepting/not accepting the null hypothesis.

29
Q

Greater the Power, greater the ____ ____

A

Sample Size

30
Q

What are the elements that determine a sample size?

A

Minimum difference between groups deemed significant

Expected variation of measurement

Alpha (type I) and Beta (type 2) error rates and confidence interval (usually ranges from 90% to 99%).

31
Q

P-value is associated with what kind of error? Type I or Type II?

A

Type I

32
Q

Levene’s Test checks for? What is null hypothesis?

A

Equality of variance

Null: There is no difference and are equal

33
Q

If Levene’s Test P-Value is less than .05 then

A

variance are not equal and do not use t-test

34
Q

What is the benefit of using confidence intervals over p-value?

A

Can infer p-value after knowing the variance and spread of data from mean.

35
Q

For a confidence interval to be statistically significant, the values MUST be

A

One one side of the ratio of 1. In other words, directional words must both be greater/greater above 1.0 or less than/less than below

36
Q

What is the relationship between confidence interval and precision?

A

If you increase the confidence interval, the precision decreases.

37
Q

What is the purpose of the correlation?

A

It provides a quantitative measure of the strength and direction of a relationship

38
Q

What are the first two question we must ask for picking a statistical test?

A

What kind of data are you collecting?

What kind of comparison/assessment is desired?

39
Q

What is the correlation test for nominal data?

A

Contingency coefficient

40
Q

What is the correlation test for ordinal data?

A

Spearman Correlation

41
Q

What is the correlation test for interval data?

A

Pearson Correlation

42
Q

What are the key words for correlation?

A

“Correlate” “Compare”

43
Q

What is the comparison or assessment type for “event or “Time-to-event”?

A

Survival Test

44
Q

What is the nominal survival test?

A

Log-Rank Test

45
Q

What is the ordinal survival test?

A

Cox-Proportional Hazard test

46
Q

What is the interval survival test?

A

Kaplan-Meier test

47
Q

Time with respect to a clock is only pertaining to which type of survival test?

A

Interval: Kaplan-Meier Test

48
Q

What is the keyword for survival test?

A

“Changes over time” “every 2 months over 36 months”

49
Q

What is the comparison or assessment for “outcome prediction or association”? It uses a prediction by utilizing multiple variables to predict an outcome

A

Regression

50
Q

What data can we obtain from a regression test?

A

Odds Ratio

51
Q

What is the nominal regression test called?

A

Logistic Regression

52
Q

What is the ordinal regression test called?

A

Multinomial logistic regression

53
Q

What is the interval regression test called?

A

Linear Regression

54
Q

What is the most common type of comparison/assessment?

A

Frequencies, Counts and Proportions

55
Q

What two additional questions need to be answered when dealing with frequencies, count and proportions?

A

How many groups?

Is the data independent or related?

56
Q

What type of test is best for frequencies, counts and proportions with 2 groups of independent data?

A

Pearson’s Chi square test

57
Q

What type of test is best for frequencies, counts and proportions with 3 or more groups of independent data?

A

Chi-square test of independence

58
Q

If you have independent data with a expected cell count of less than 5 for frequencies, counts and proportions we should use?

A

Fischer’s Exact Test

59
Q

What are buzzwords for related or paired frequencies, counts and proportions tests?

A

“pre vs post”
“baseline vs end”
“before vs end.”

60
Q

For statistically significant findings in 3 or more comparisons, one must perform ____ to determine which groups are different. Specifically, ____ to avoid _____.

A

Post-hoc testing
Bonferroni test of inequality
Risk of increasing type I error

61
Q

For 2 groups of paired/related frequencies, counts and proportions we would use?

A

McNemar

62
Q

For 3 or more groups of paired/related frequencies, counts and proportions we would use?

A

Cochran

Epidemiology Exam 3 (2 decks)

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