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COB - Epidemiology > Exam 3 - Biostatistical Tests > Flashcards

Exam 3 - Biostatistical Tests Flashcards

1
Q

A research perspective which states there will be no true difference between the groups being compared.

A

Null hypothesis

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2
Q

Three attributes that differ between nominal/ordinal/interval/ratio data.

A

Order/magnitude, spacing/scale, rational absolute zero

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3
Q

Does nominal data have magnitude? Does nominal data have a consistent scale?

A

No; No

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4
Q

Does ordinal data have magnitude? Does ordinal data have a consistent scale?

A

Yes (i.e. it can be ordered); No (example = satisfaction survey)

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5
Q

Does interval/ratio data have magnitude? Does interval/ratio data have a consistent scale?

A

Yes; Yes (Tigger/Buzz = Units)

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6
Q

Black

A

Nominal

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7
Q

Red

A

Ordinal

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8
Q

Orange

A

Interval

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9
Q

Yellow

A

Ratio

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10
Q

True/False: After data collection you can move up (i.e. nominal => ordinal => interval => ratio) is specificty.

A

False, you may only move down

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11
Q

Average of the squared-differences in each individual measure value (x) and the groups’ mean.

A

Variance

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12
Q

Square root of variance value

A

Standard deviation

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13
Q

In a normal distribution curve the first standard deviation represents how much of the data?

A

68%

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14
Q

In a normal distribution curve the second standard deviation represents how much of the data?

A

95%

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15
Q

In a normal distribution curve the third standard deviation represents how much of the data?

A

99.7%

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16
Q

Statistical test useful for normally-distributed data.

A

Parametric (i.e. associated with interval/ratio data)

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17
Q

Data distribution, asymmetrical, mean > median, tail points right

A

Positively skewed

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18
Q

Data distribution, asymmetrical, mean < median, tail points left

A

Negatively skewed

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19
Q

Skewness value of 0.

A

Symmetrical data distribution (i.e. not skewed)

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20
Q

Positive skewness value.

A

Positively skewed

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21
Q

Negative skewness value.

A

Negatively skewed

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22
Q

Numerical value that evaluates how aggregated a data set may be (i.e. how clusted the data is)

A

Kurtosis (i.e. + = more cluster)

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23
Q

Four key questions for selecting the correct statistical test.

A
  1. What data level is being recorded? (i.e. nominal, ordinal, interval/ratio)
  2. What type of comparison/assessment is desired?
  3. How many groups are being compared?
  4. Is the data independent or related/paired?
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24
Q

Buzz words for correlation statisical test.

A

Correlation, association, relationship

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25
Q

Buzz words for regression statistical test.

A

Prediction, association, relationship.

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26
Q

Statisical test that derives a quantitative measure of strength and direction between the relationship of two variables.

A

Correlation

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27
Q

Nominal correlation test.

A

Contingency Coefficent

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28
Q

Ordinal correlation test.

A

Spearman Correlation

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29
Q

Interval/ratio correlation test.

A

Pearson correlation

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30
Q

A correlaiton that controls for confounding variables (i.e. only for interval data)

A

Partial correlation

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31
Q

A correlation test, shows relationship of agreement between/consistency of “decisions”.

A

Kappa statistic

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32
Q

+1 Kappa value.

A

Observers all classify everyone the same way.

33
Q

0 Kappa value.

A

There is no relationship.

34
Q

-1 Kappa value.

A

Observers classify everyone exactly the opposite of each other.

35
Q

Statistical test, provides a measure of the relationship between variables by allowing the predictions about the dependent/outcome variable knowing the value/catergoy of independent variables.

A

Regression

36
Q

Nominal regression test.

A

Logisitic regression

37
Q

Ordinal regression test.

A

Multinomial logisitic regression

38
Q

Interval/ratio regression test.

A

Linear regression

39
Q

Statistical test, compare the proportion of events over time/time-to events between groups (ongoing progression)

A

Survival test

40
Q

Common representation of survival tests.

A

Kaplan-Meir curve

41
Q

Survival test for nominal data.

A

Log-Rank test

42
Q

Survival test for ordinal data.

A

Cox-Proportional Hazards test

43
Q

Survival test for interval data.

A

Kaplan-Meier test.

44
Q

Buzz saying for survival test.

A

“Over time”

45
Q

Statistical test for independent nominal data comparing two groups (i.e. for a normal to large set of data)

A

Chi-Square

46
Q

Statistical test for independent nominal data comparing two groups (i.e. for smaller set of data).

A

Fisher’s Exact Test

47
Q

Statistical test for independent nominal data comparing 3+ groups (i.e. from a normal-large data set).

A

Chi-square

48
Q

Statistical test for independent nominal data comparing 3+ groups (i.e. from a smaller data set).

A

Fisher’s Exact

49
Q

Post-hoc test, adjusts the p value for # of comparisons being made.

A

Bonferroni test of Inequality

50
Q

Statistical test for paired/related nominal data comparing 2 groups.

A

McNemar Test

51
Q

Statistical test for paried/related nominal data comparing 3+ groups.

A

Cochran

52
Q

Statistical test for independent ordinal data comparing 2 groups.

A

Mann-Whitney test

53
Q

Statistical test for independent ordinal data comparing 3+ groups.

A

Kruskal-Wallis test

54
Q

What value/measurement is being compared in the ordinal group comparison tests?

A

Median values between groups

55
Q

Statistical test for paired/related ordinal data comparing 2 groups.

A

Wilcoxon Signed Rank test

56
Q

Statistical test for pair/related ordinal data comparing 3+ groups.

A

Friedman test

57
Q

Post-hoc test, 3+ groups, ordinal data, compares all pairwise comparisons possible, and all groups must be equal in size.

A

Student-Newman-Keul test

58
Q

Post-hoc test, 3+ groups, ordinal data, compares all pairwise comparisons againsts a singe control, and all groups must be equal in size.

A

Dunnett test

59
Q

Post-hoc test, 3+ groups, ordinal data, compares all pairwise comparisons possible, and useful when all groups are not of equal size.

A

Dunn test

60
Q

Statistical test for independent interval data comparing 2 groups.

A

Student t-test

61
Q

Statistical test for independent interval data comparing 3+ group.

A

Analysis of Variance (ANOVA)

62
Q

What value/measurement is being compared in interval data group comparison tests?

A

Means of all groups

63
Q

Statisical test for paired/related interval data comparing 2 groups.

A

Paired t-test

64
Q

Statistical test for paired/related interval data comparing 3+ groups.

A

ANOVA

65
Q

Post-hoc test, 3+ groups, interval data, compares all pairwise comparisons possible, and all groups must be equal in size.

A

Student-Newman-Keul test

66
Q

Post-hoc test, 3+ groups, interval data, compares pairwise comparisons against a single control, and all groups must be equal in size.

A

Dunnett test

67
Q

Post-hoc test, 3+ groups, interval data, compares all pairwise comparisons possible, useful when all groups are not of equal size.

A

Dunn test

68
Q

Post-hoc test, 3+ groups, interval data, compares all pairwise comparisons possbile, all groups must be equal in size, and slightly more conservative than the Student-Newman-Keul test.

A

Tukey test

69
Q

Post-hoc test, 3+ groups, interval data, compares all pairwise comparisons possible, all groups must be equal in size, and less affected by violations in normality and homogeneity of variances (i.e. than Tukey or Student-Newman-Keul test).

A

Scheffe test (i.e. most conservative)

70
Q

Statistical test, interval data, determines if variances are equal between groups.

A

Levene’s test

71
Q

How can interval/ratio data be delt with when it is not normally distributed?

A

Transform to standardized value (i.e. z-score or log transformation) or drop down to ordinal data and use odrinal test.

72
Q

Guide for determining whether we accept/reject null hypothesis.

A

Statistical tests

73
Q

Not accepting the Null hypothesis when it is TRUE.

A

Type I error

74
Q

Accepting the Null hypothesis when it is FALSE.

A

Type II error

75
Q

Probability that differences in group is due to chance. Probabily of making a type I error had you claimed there was a difference.

A

P value

76
Q

A studies ability to find differences between groups.

A

Power

77
Q

True/False: More people in a data set increases power of a study.

A

True

78
Q

Things to consider when determining sample size.

A

How small is the difference between groups being determined, expected variation of measurement, and Type I and Type II Error Rate or Confidence Interval.

79
Q
A

COB - Epidemiology (3 decks)

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