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Epidemiology > Exam 3 > Flashcards

Exam 3 Flashcards

1
Q

Data will be collected on desired ________, both dependent (outcome) and independent.

A

Variables

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2
Q

The 3 primary levels (groupings) for variables (data) are…

A

1) Nominal
2) Ordinal
3) Interval or Ratio

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3
Q

The 3 primary levels are based on 3 key attributes, which are…

A

1) Order/Magnitude
2) Consistency of scale/ Equal distances
3) Rational absolute zero

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4
Q

This primary level has NO order/magnitude, NO consistency of scale/equal distances, and is based on named categories. Dichotomous/binary; Non-ranked.

A

Nominal

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5
Q

If something has order/magnitude, but only has 2 categories, then it is ALWAYS (NOMINAL/ORDINAL).

A

Nominal

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6
Q

This primary level has order/magnitude, but NO consistency of scale/equal distances. It is ordered, rank-able categories.

A

Ordinal

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7
Q

This primary level has order/magnitude and equal distances (units).

A

Interval/Ratio

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8
Q

(INTERVAL/RATIO) has an arbitrary zero value (0 doesn’t mean absence, it can go negative); (INTERVAL/RATIO) has an absolute zero value (0 means absence of measurement value, it can NOT go negative).

A

Interval; Ratio

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9
Q

Which primary levels are considered ‘discrete’ or ‘continuous’?

A

Nominal and Ordinal = Discrete

Interval/Ratio = Continuous

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10
Q

ALL statistical _____ are selected based on the level of data being compared.

A

Tests

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11
Q

After data is collected, we can appropriately go (UP/DOWN) in specificity/detail of data measurement levels, but we can never go (UP/DOWN).

A

Down; Up

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12
Q

________ statistics are non-comparative, simple description of various elements of the study’s data.

A

Descriptive

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13
Q

Examples of descriptive statistics, measures of central tendency (dispersion or spread) are _____/_____/_____; ______/______/______; and ________ ________.

A

Mode/Median/Mean
Minimum/Maximum/Range
Interquartile Range (IQR)

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14
Q

Interquartile range is the middle ___% of the data.

A

50%

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15
Q

The average of the squared-differences in each individual measurement value (x) and the groups’ mean is called…

A

Variance

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16
Q

The square root of the variance value (restores units of mean) is called…

A

Standard Deviation (SD)

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17
Q

Stats tests useful for normally-distributed data are called _________ tests.

A

Parametric

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18
Q

_______ representations shows the shape of data (i.e., bell curve).

A

Graphical

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19
Q

Normally distributed data is considered (SYMMETRICAL/ASYMMETRICAL).

A

Symmetrical

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20
Q

What a dataset is normally-distributed the following values (parameters) are equal/near equal…

A

Mean and Median

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21
Q

A standard deviation of +/- 1 from the mean is ____%.

A

68%

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22
Q

A standard deviation of +/- 2 from the mean is ____%.

A

95%

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23
Q

A standard deviation of +/- 3 from the mean is ____%.

A

99.7%

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24
Q

A (POSITVELY/NEGATVELY) skewed graph is when the mean is higher than the median, and the tail (on graph) points to the right.

A

Positively

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25
Q

Skewed data distribution is considered (SYMMETRICAL/ASYMMETRICAL), with one ‘tail’ longer than another on the graph. A distribution is skewed anytime the median differs from the mean.

A

Asymmetrical

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26
Q

A (POSITIVELY/NEGATIVELY) skewed graph is the when the mean is lower than the median, and the tail (on graph) points to the left.

A

Negatively

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27
Q

This is a measure of the asymmetry of a distribution. The perfectly-normal distribution is symmetric and would have a value of 0 with this measurement.

A

Skewness

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28
Q

T/F. A non-zero skewness value DOES NOT mean it’s skewed.

A

True

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29
Q

This is a measure of the extent to which observations cluster around the mean. For a normal distribution, the value is 0.

A

Kurtosis

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30
Q

A positive kurtosis means there is (MORE/LESS) cluster, and a negative kurtosis means there is (MORE/LESS) cluster.

A

More; Less

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31
Q

What are the 3 required assumptions of interval/ratio data for proper selection of a parametric test?

A

1) Normally-distributed
2) Equal variances
3) Randomly-derived and Independent

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32
Q

What test is used to assess for equal variances between groups?

A

Levene’s Test

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33
Q

How is interval data handled that is NOT normally-distributed?

A

1) Use statistical test that does not require it to be normally-distributed

(OR)

2) Transform data to a standardized value (hoping this makes data normally-distributed)

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34
Q

This is a research perspective that states there will be NO true difference between the groups being compared. It is the most conservative and commonly utilized.

A

Null Hypothesis (H0)

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35
Q

This type of error is NOT accepting the null hypothesis when it is actually true, and you should have accepted it. There really was no true difference between groups but you believed there was a difference.

A

Type 1 Error (Alpha)

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36
Q

This type of error is accepting the null hypothesis when it is actually false, and you should NOT have accepted it. There really is a true difference between groups but you believed there was no difference.

A

Type 2 Error (Beta)

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37
Q

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

A

Power (1-Beta)

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38
Q

T/F. The larger the sample size, the greater the likelihood (ability) of detecting a difference if one truly exists.

A

True

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39
Q

The larger the sample size, then there is a(n) (INCREASE/DECREASE) in power.

A

Increase

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40
Q

We accept a ____% risk of making Type 2 errors (___% power).

A

20%; 80%

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41
Q

We accept a ____% risk of making Type 1 errors (____% power).

A

5%; 95%

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42
Q

The 3 things that determine sample size are –

1) (MINIMUM/MAXIMUM) difference between groups deemed significant
2) Expected variation of measurement
3) Type 1 (alpha) and Type 2 (beta) error rates and confidence interval (ranges from 90%-99%

A

Minimum

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43
Q

The (SMALLER/LARGER) the difference between groups necessary to considered “significant”, the greater the sample size is needed.

A

Smaller

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44
Q

If the p-value is lower than the pre-selected alpha (Type 1) value (customarily 5% (0.05)) then we say it (IS/IS NOT) statistically significant.

A

Is

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45
Q

If the p-value is less than the alpha percentage-risk error (5%), then we (REJECT/ACCEPT) the null hypothesis.

A

Reject

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46
Q

Interpretation of a pre-set (a priori) p-value —- The probability of making a Type 1 error if the null hypothesis is (ACCEPTED/REJECTED).

A

Rejected

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47
Q

If we are interpreting the p-value for more than 2 categories, then we focus on the ______ and ______ values to prove a difference.

A

Lowest; Highest

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48
Q

The 2 times we want there to be NO statistical difference (accept null hypothesis) is when there is —

1) ________ data - starting out
2) In a _______ test

A

Baseline; Levene’s

49
Q

If the p-value is 0.91 and you say there IS a significant difference, then you have a ____% chance of committing a Type 1 error.

A

91%

50
Q

When groups are equal, the p-value is ____.

A

1

51
Q

In interval data, we use the Levene’s test to assess for equal variances between groups. If there IS a difference (not equal variances) then we do not use the next test, called the _______.

A

T-Test

52
Q

If you don’t use the same ________ words for confidence interval (CI), then it is not statistically significant.

A

Directional

53
Q

Journals are moving away from solely reporting ______, or even showing them at all.

A

P-values

54
Q

If a confidence interval crosses ____ for ratios (RR/OR/HR) or _____ for absolute differences, then they are NOT significant.

A

1.0; 0.0

55
Q

P-values can only tell us if data is statistically significant, but _______ _______ can tell us if data is statistically significant and the range group where the difference might lie.

A

Confidence Interval (CI)

56
Q

When reviewing the findings of a study, what question should ALWAYS be asked?

A

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

57
Q

What is the 1st question that must be asked when selecting the correct statistical test?

A

What data level is being recorded? (nominal, ordinal or interval)

58
Q

What is the 2nd question that must be asked when selecting the correct statistical test?

A

What type of comparison/assessment is desired?

59
Q

This type of statistical test provides a quantitative measure of the strength and direction of a relationship between variables. Values range from -1.0 to +1.0

A

Correlation test

60
Q

A ______ correlation is a correlation that controls for confounding variables.

A

Partial

61
Q

When there is a positive correlation of exactly +1.0, then the graph will display a ____ degree line in the positive direction.

A

45

62
Q

When there is a negative correlation of exactly -1.0, then the graph will display a ____ degree line in the negative direction.

A

45

63
Q

What is the name for a nominal correlation test?

A

Contingency coefficient

64
Q

What is the name for an ordinal correlation test?

A

Spearman correlation

65
Q

What is the name for an interval correlation test?

A

Pearson correlation

66
Q

In the interval correlation test (Pearson correlation) a p value > 0.05 means there is no ________ correlation. There may still be ________ correlations present.

A

Linear; Non-linear

67
Q

This type of statistical test compares the proportion of events over time, or time-to events, between groups.

A

Survival test

68
Q

What can all survival tests be represented by graphically?

A

Kaplan-Meier curve

69
Q

What is the name of the nominal survival test?

A

Log-Rank test

70
Q

What is the name of the ordinal survival test?

A

Cox-Proportional Hazards test

71
Q

What is the name of the interval survival test?

A

Kaplan-Meier test

72
Q

This type of statistical test provides a measure of the relationship between variables by allowing the prediction about the dependent, or outcome, variable knowing the value/category of independent variables. Also able to calculate OR for a measure of association.

A

Regression test

73
Q

What is the name of a nominal regression test?

A

Logistic regression

74
Q

What is the name of an ordinal regression test?

A

Multinomial Logistic regression

75
Q

What is the name of an interval regression test?

A

Linear regression

76
Q

When the answer to the 2nd question of selecting the correct statistical test is “frequencies/counts/proportions” then there must be 2 follow up questions after (3rd and 4th question), which are…

A

3) How many groups are being compared?

4) Is the data independent or related (paired)?

77
Q

If you have 2 groups of independent nominal data, then you use which test?

A

Pearson’s Chi-square test

78
Q

If you have 3 or more groups of independent nominal data, then you use which test?

A

Chi-square test of independence

79
Q

What type of test has a skewed curve and compares “should have expected” from the real value?

A

Chi-square test

80
Q

If you have independent nominal data with 2 or more groups with an expected cell count of less than 5, which test should you use?

A

Fisher’s Exact test

81
Q

For statistically significant data (in all data types) of 3 or more comparisons, you have to perform post-hoc testing to determine which tests are different. With nominal data, you use which post-hoc test?

A

Bonferroni test of inequality (Bonferroni correction)

82
Q

If you have paired/related nominal data with 2 groups, which test should you use?

A

McNemar test

83
Q

If you have paired/related nominal data with 3 or more groups, which test should you use?

A

Cochran test

84
Q

If you have 2 groups of independent ordinal data, which test do you use?

A

Mann-Whitney test

85
Q

If you have 3 or more groups of independent ordinal data, which test do you use?

A

Kruskal-Wallis test

86
Q

If you have 3 or more groups of ordinal data (independent or paired/related) and it is statistically significant, you must do a post-hoc test. Ordinal has 3 possible post-hoc tests, which are…

A

Student-Newman-Keul test
Dunned test
Dunn test

87
Q

This ordinal/interval post-hoc test is used to compare all pairwise comparisons possible. All groups must be equal in size.

A

Student-Newman-Keul test

88
Q

This ordinal/interval post-hoc test is used to compare all pairwise comparisons against a single control (i.e., center of pinwheel). All groups must be equal in size.

A

Dunnett test

89
Q

This ordinal/interval post-hoc test is used to compare all pairwise comparisons possible. Useful when all groups are NOT of equal size. (Good for lost-to-follow-ups)

A

Dunn test

90
Q

Ordinal data tests compare the (MEAN/MEDIAN) between groups, while the interval data tests compare the (MEAN/MEDIAN) between groups.

A

Median; Mean

91
Q

If you have 2 groups of paired/related ordinal data, then which test is used?

A

Wilcoxon Signed Rank test

92
Q

If you have 3 groups of paired/related ordinal data, then which test is used?

A

Friedman test

93
Q

If you have 2 groups of independent interval data, which test is used?

A

Student t-test

94
Q

If you have 3 or more groups of independent interval data, which test is used?

A

Analysis of Variance (ANOVA)

95
Q

If you have 3 or more groups of independent interval data with confounders, which test is used?

A

Analysis of Co-Variance (ANCOVA)

96
Q

If you have 2 groups of paired/related interval data, which test is used?

A

Paired t-test

97
Q

If you have 3 or more groups of paired/related interval data, which test is used?

A

Repeated Measures ANOVA (1 DV)

98
Q

If you have 3 or more groups of paired/related interval data with confounders, which test is used?

A

Repeated Measures ANCOVA

99
Q

If you have 3 or more groups of interval data (independent or paired/related) and it is statistically significant, you must do a post-hoc test. Interval has 5 possible post-hoc tests, which are…

A 
Student-Newman-Keul test
Dunnett test
Dunn test 
Tukey (or) Scheffe tests 
Bonferroni correction
100
Q

This interval post-hoc test compares all pairwise comparisons possible. All groups must be equal in size. One is slightly more conservative than Stu-N-K and the other is less affected by violations in normality and homogeneity of variances, which makes it the most conservative.

A 
Tukey test 
Scheffe test (most conservative)
101
Q

This interval post-hoc test adjusts the p-value for the number of comparisons being made. It is very conservative.

A

Bonferroni correction

102
Q

This is a type of correlation test showing relationship or agreement between evaluators (consistency of “decisions” or “determinations”).

A

Kappa statistic

103
Q

In a kappa interpretation, this means the observers perfectly “classify” everyone exactly the same way.

A

+1

104
Q

In a kappa interpretation, this means there is no relationship at all between the observers’ “classifications”, above the agreement would be expected by chance.

A

0

105
Q

In a kappa interpretation, this means the observers “classify” everyone exactly the opposite of each other.

A

-1

106
Q

Kappa (K) value can be a + or - . + = (GOOD/POOR) agreement, and - = (GOOD/POOR) agreement.

A

Good; Poor

107
Q

This is a unique identifier number assigned by clinical trials.gov once research protocol is submitted prior to study initiation. Its purpose is to reduce publication bias.

A

National Clinical Trials (NCT) number

108
Q

This gives us a digital number to go find where an article is found on the web. It will take you directly to the article, especially from references.

A

DOI

109
Q

This checklist is used for randomized interventional trials/studies.

A

CONSORT (Consolidated Standards of Reporting Trials)

110
Q

This checklist is used for systematic reviews of multiple randomized trials (interventional).

A

PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses)

111
Q

This checklist is used for observational studies (cohort, case-control, cross-sectional).

A

STROBE (Strengthening the Reporting of Observational Studies in Epidemiology)

112
Q

This checklist is for molecular epidemiology observational studies.

A

STROBE-ME

113
Q

This checklist is for genetic association observational studies.

A

STREGA (Strengthening the Reporting of Genetic Association studies)

114
Q

This checklist is for reporting evaluations with non-randomized designs of behavioral and public health interventions.

A

TREND (Transparent Reporting of Evaluations with Non-randomized Designs)

115
Q

This checklist is for tumor marker prognostic studies.

A

REMARK (Reporting Recommendations for Tumor Marker Prognostic studies)

116
Q

This checklist is for genetic risk prediction studies.

A

GRIPS (Genetic Risk Prediction Studies)

117
Q

This checklist is for diagnostic studies.

A

STARD (Standards for the Reporting of Diagnostic Accuracy studies)

118
Q

This checklist is for the systematic reviews of multiple diagnostic studies.

A

QUADAS-2 (Quality Assessment of Studies of Diagnostic Accuracy in Systematic Reviews)

Epidemiology (3 decks)

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