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Epidemiology Exam 3 > Intro to Biostatistics > Flashcards

Intro to Biostatistics Flashcards

1
Q

Dependent Variable

A

Outcome you are measuring or looking for

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2
Q

Independent Variable

A

What is manipulated/changed during an experiment or study

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3
Q

Null Hypothesis (H0)

A

States there will be no true difference between the groups being compared

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4
Q

Alternative Hypothesis (H1)

A

States there will be a true difference between the groups being compared

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5
Q

Nominal Grouping

A

Dichotomous/binary; non-ordered, named categories; no order or magnitude, no consistency of scale or equal distances; simply labeled variables without quantitative characteristics

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6
Q

Ordinal Grouping

A

Ordered, rank-able categories; non-equal distance; they have order/magnitude but have NO consistency of scale or equal distances

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7
Q

Interval/Ratio Grouping

A

Ordered, magnitude, and equal distances/units; have order/magnitude AND consistency of scale/equal distances

Ex: Living siblings (number) and personal age (in years)

Interval: Arbitrary zero value (but 0 doesn’t mean absence)

Ratio: Absolute rational zero value (0 DOES mean absence of measurement value)

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8
Q

Which groups are considered “discrete” data?

A

Nominal and Ordinal

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9
Q

Which groups are considered “continuous” data?

A

Interval/Ratio

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10
Q

Mode

A

Most common number

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11
Q

Median

A

Middle number after numbers are placed in order

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12
Q

Mean

A

Average of all numbers

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13
Q

Minimum, Maximum, Range

A 
Minimum = lowest
Maximum = highest
Range = difference between min and max
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14
Q

Variance

A

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

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15
Q

Standard Deviation

A

Square root of variance value

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16
Q

When a dataset is normally distributed, which values are equal or near equal?

A

Mean and Median

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17
Q

1 standard deviation is what percentage under the curve?

A

68%

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18
Q

2 standard deviations is what percentage under the curve?

A

95%

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19
Q

3 standard deviations is what percentage under the curve?

A

99.7%

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20
Q

Positively Skewed

A

When mean is higher than median; tail is pointing to the right

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21
Q

Negatively Skewed

A

When mean is lower than the median; tail is pointing to the left

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22
Q

Kurtosis

A

Measure of the extent to which observations cluster around the mean; for a normal distribution, the value of the kurtosis statistic is 0

Positive Kurtosis = more cluster
Negative Kurtosis = less cluster

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23
Q

Skewness

A

Measure of the asymmetry of a distribution

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24
Q

Required assumptions of Interval/Ratio data for the proper selection of a parametric test

A
  1. Normally distributed
  2. Equal variances (multiple tests available for equal variances between groups)
  3. Randomly-derived and independent
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25
Q

Levene’s Test

A

Test that tells us if data is normally distributed or not and if it has equal variances

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26
Q

How do you handle data that is NOT normally-distributed?

A

Use a statistical test that does not require the data to be normally distributed, such as ordinal or nominal tests, or transform data to a standardized value with the hope that this transformation allows data to be normally-distributed (may not work)

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27
Q

Type 1 Error

A

NOT accepting the null hypothesis when it is actually true and should have been accepted; there really is no true differences between the groups; also called “alpha”

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28
Q

Type 2 Error

A

Accepting the null hypothesis when it is actually false, and you should NOT have accepted it; there really IS a true difference between the groups being compared; also called “beta”

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29
Q

Power

A

1-beta; 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

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30
Q

Sample Size

A

The larger the sample size, the greater the likelihood (ability) of detecting a difference if one truly exists; also increases power

31
Q

P Value

A

Statistical tests determine possible error-rate or likelihood of chance in comparing difference or relationship between variables

32
Q

Confidence Interval (CI)

A

Most common selections are 90, 95, or 99%; calculated at an a priori percentage of confidence that statistically includes the real (yet unknown) difference or relationship being compared; based on variation in sample and sample size

33
Q

Interpretation of a 95% CI

A

We are 95% confident that the “true” difference or relationship between the groups is contained within the confidence interval range

34
Q

What does it mean when a CI crosses 1.0 for ratios or 0.0 for absolute differences?

A

Means that CI is NOT significant

35
Q

Does “statistical” significance always confer meaningful, “clinical” significance?

36
Q

Correlation (r)

A

Provides a quantitative measure of the strength and direction of a relationship between variables; values range from -1.0 - 1.0

37
Q

Partial Correlation

A

A correlation that controls for confounding variables

38
Q

What is the name of the nominal correlation test?

A

Contingency coefficient

39
Q

What is the name of the ordinal correlation test?

A

Spearman correlation

40
Q

What is the name of the interval correlation test?

A

Pearson correlation; for a pearson correlation, a p value of >0.05 means there is no linear correlation, but there MAY still be a non-linear correlation present

41
Q

Survival Tests

A

Compares the proportion of events over time, or time-to events, between groups; commonly represented by a Kaplan-Meier Curve

42
Q

What is the name of the nominal survival test?

A

Log-Rank Test

43
Q

What is the name of the ordinal survival test?

A

Cox-Proportional Hazards Test

44
Q

What is the name of the interval survival test?

A

Kaplan-Meier Test

45
Q

Regressions

A

Provide a measure of the relationship between variables by allowing the prediction about the dependent, or outcome, variable (DV) knowing the value/category of independent variables (IVs); can also calculate OR for a measure of association

46
Q

What is the name of the nominal regression test?

A

Logistic Regression

47
Q

What is the name of the ordinal regression test?

A

Multinomial Logistic Regression

48
Q

What is the name of the interval regression test?

A

Linear Regression

49
Q

What are the 4 questions you should ask when selecting the correct statistical test?

A
  1. What data level is being recorded?
  2. What type of comparison/ assessment is desired?
  3. How many groups are being compared?
  4. Is the data independent or related/paired?
50
Q

What is the name of the nominal test when comparing 2 groups of independent data?

A

Pearson’s Chi-Square Test

51
Q

What is the name of the nominal test when comparing 3 or more groups of independent data?

A

Chi-Square Test of Independence

52
Q

What is the name of the nominal test when comparing 2 or more groups of independent data that have an expected cell count of less than 5?

A

Fisher’s Exact Test

53
Q

What is the name of the nominal post-hoc test?

A

Bonferroni Test of Inequality (Bonferroni Correction); adjusts p value for # of comparisons being made

54
Q

What is the name of the nominal test when comparing 2 groups of related data?

A

McNemar Test

55
Q

What is the name of the nominal test when comparing 3 or more groups of related data?

56
Q

What is the name of the ordinal test when comparing 2 groups of independent data?

A

Mann-Whitney Test

57
Q

What is the name of the ordinal test when comparing 3 or more groups of independent data?

A

Kruskal-Wallis Test

58
Q

What is the name of the ordinal test when comparing 2 groups of related data?

A

Wilcoxon Signed Rank Test

59
Q

What is the name of the ordinal test when comparing 3 or more groups of related data?

A

Friedman Test

60
Q

What are the names of the ordinal post-hoc tests?

A

Student-Newman-Keul, Dunnett, Dunn

61
Q

Student-Newman-Keul Test

A

Compares all pairwise comparisons possible and all groups must be equal in size

62
Q

Dunnett Test

A

Compares all pairwise comparisons against a single control and all groups must be equal in size

63
Q

Dunn Test

A

Compares all pairwise comparisons possible and it is useful when all groups are not of equal size

64
Q

What is the name of the interval test when comparing 2 groups of independent data?

A

Student T-Test

65
Q

What is the name of the interval test when comparing 3 or more groups of independent data?

A

Analysis of Variance (ANOVA)

66
Q

What is the name of the interval test when comparing 3 or more groups of independent data with confounders?

A

Analysis of Co-Variance (ANCOVA); compares the means of all groups against a dependent variable while also controlling for the co-variance of confounders

67
Q

What is the name of the interval test when comparing 2 groups of related data?

A

Paired T-Test

68
Q

What is the name of the interval test when comparing 3 or more groups of related data?

A

Repeated Measures ANOVA with 1 dependent variable

69
Q

What is the name of the interval test when comparing 3 or more groups of related data with confounders?

A

Repeated Measures ANCOVA; compares the means of all groups against a dependent variable while also controlling for the co-variance of confounders

70
Q

What are the names of the interval post-hoc tests?

A

Student-Newman-Keul, Dunnett, Dunn, Tukey or Scheffe, and Bonferroni Correction

71
Q

Tukey/Scheffe Tests

A

Compares all pairwise comparisons possible and all groups must be equal in size; tukey test is slightly more conservative than the SNK; scheffe test is less affected by violations in normality and homogeneity of variances - most conservative

72
Q

Kappa Statistic

A

Correlation test showing relationship or agreement between evaluators (consistency of “decisions” or “determinations”)

73
Q

Interpreting a Kappa Statistic

A

+1 - observers perfectly “classify” everyone exactly the same way
0 - there is no relationship at all between the observers “classifications”, above the agreement that would be expected by chance
-1 - observers “classify” everyone exactly the opposite of each other

Epidemiology Exam 3 (1 decks)

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