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Epidemiology- Erin > Exam III > Flashcards

Exam III Flashcards

1
Q

What are the two key attributes of data measurement (variable)?

A
  1. magnitude

2. consistency of scale/ fixed interval

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2
Q

What is the third variable used to assess data when the first two are answered with yes’?

A

-rational/absolute zero

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3
Q

What are the three levels of measurement?

A
  • nominal
  • ordinal
  • interval
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4
Q

Examples of nominal measurements

A

-variables that are simply labeled variables without quantitative characteristics

  • gender
  • hair color
  • occupation
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5
Q

examples of ordinal variables

A

-variables that have magnitude but no consistency of scale

  • interval of ages (1-18, 19-50)
  • months homeless (less than three, greater than three)
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6
Q

examples of interval data

A

-number with units at the end

  • age
  • number of siblings
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7
Q

What variables are considered discrete vs continuous?

A

discrete: nominal, ordinal
continuous: interval

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8
Q

What are the measures of central tendency utilized for describing continuous data?

A
  • mode/mean/median
  • outliers
  • min/max/range
  • interquartile range
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9
Q

What is variance?

A

difference in each individual measurement value and the groups’ mean

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10
Q

What is standard deviation?

A
  • square root of variance value

- know eqn

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11
Q

How do you know when a graph is normally distributed?

A

-the mean/median/mode are near equal

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12
Q

What are parametric tests?

A

-stats tests useful for normally distributed data

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13
Q

What are the two types of graphical shapes?

A
  • positively skewed

- negatively skewed

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14
Q

How can you tell the difference between a positively and negatively skewed graph based on stats alone?

A

positively skewed:
- mean is greater than median

negatively skewed:
-mean is less than median

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15
Q

Definition of skewness

A

-a measure of asymmetry of a distribution

+a perfectly normal distribution is symmetric and has a skewness value of 0

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16
Q

What is kurtosis?

A
  • a measure of the extent to which observations cluster around the mean. For a normal distribution, the value of the kurtosis statistic is 0.
  • how peaked the graph is
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17
Q

positive vs negative kurtosis

A

positive -> more cluster

negative -> less cluster

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18
Q

What do you get when you add or subtract a std dev from the mean?

A

-range of middle 68%, 95%, and 99%

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19
Q

What are the required assumptions for interval data to select a parametric test?

A
  1. normally distributed
  2. equal variances
    +Levene’s test
  3. randomly derived and independent
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20
Q

What is the Levene’s test?

A

-a test for variablity

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21
Q

How does one handle interval data that is not normally distributed?

A
  • use a statistical test that does not require the data to be normally distributed (non-parametric)
  • transform data to a standardized value (z-score or log)
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22
Q

What is power?

A

1-beta (type 2 error)

  • the ability of a study design, its methodology, and the selected test statistic to detect a true difference if one truly exists between group comparisons (analogous to sensitivity)
  • researchers typically choose 80% power to truly distinguish a difference between two groups
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23
Q

What does power have to do with sample size?

A

-the larger the sample size, the greater the likelihood of detecting a difference if one truly exists (increase in power)

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24
Q

What needs to be determined with each sample? (for size)

A
  1. minimum difference between groups deemed significant
    +the smaller the difference between groups necessary to be considered significant, the greater the N needed
  2. expected variation of measurement
  3. alpha and beta error rates
    +alpha -> type 1 (5%)
    +beta -> type 2 (20%)
    +add in anticipated drop outs or loss to follow ups
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25
Q

What is the p value and why is it important?

A

-statistical tests that determine the possible differences or relationships between variables
-same as type 1 error and alpha
-if less than 0.05, then you can claim there is a difference between groups
+small chance that the difference didn’t occur by chance

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26
Q

When the p value is high which hypothesis will you be more likely to accept?

A

null hypothesis

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27
Q

What is type 1 error (alpha)?

A
  • false positive

- rejecting the null hypothesis when it is actually true

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28
Q

What is type 2 error (beta)?

A
  • false negative

- accepting the null hypothesis when you should have rejected it

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29
Q

When comparing baseline characteristics in a study what you want the p values to be?

A
  • high p values, want no difference between groups

- same for Levene’s test for baseline

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30
Q

How would one interpret the p value in words?

A

-probability of making a type 1 error if null is rejected

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31
Q

What is the confidence interval?

A

-percentage of confidence that statistically the real difference or relationship resides
-based on:
+variation in sample (v/sd)
+sample size

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32
Q

What is the most commonly selected percentage for a CI?

A

95%

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33
Q

How is a CI interpreted?

A

-we are 95% confident that the true difference/relationship between the groups is contained within the confidence interval range

34
Q

How are CI interpreted without the p value?

A
  • if CI crosses 1.0 (OR/RR/HR) or 0.0 (other), then the groups are not significant
  • same as if p were greater than 0.05
35
Q

CI on a Forest plot

A

-the error bars represent the CI

36
Q

What are the 4 key questions for selecting the correct statistical test? Which two are more for comparing frequencies?

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

-3,4 deal with frequency comparisons

37
Q

What are the different types of comparisons/assessments?

A
  • correlations
  • event-occurrence/time to event -> survival test
  • outcome prediction/association (OR) -> regression
38
Q

What is a correlation?

A

-provides a quantitative measure of the strength and direction of a relationship between variables
-values range from -1 to 1
+perfectly negative = -1
+perfectly positive = +1

39
Q

What is a partial correlation?

A

-a correlation that controls for confounding variables

40
Q

What are the difference correlation tests that can be run for each individual data type?

A

nominal -> contingency coefficient

ordinal -> spearman correlation

interval -> pearson correlation

41
Q

What does a greater than 0.05 for a Pearson correlation mean?

A

-there is no linear correlation, there can still be non-linear correlations present

42
Q

What are survival tests?

A

-compares the proportion of, or time to, event occurrences between groups

43
Q

What are the different survival tests for the types of data?

A

nominal -> log-rank test

ordinal -> cox-proportional hazards test

interval -> Kaplan-Meier test

*all can be represented by a Kaplan-Meier curve

44
Q

What is a regression? What can be calculated from this type of test?

A
  • provide a measure of the relationship between variables by allowing the prediction about the dependent, or outcome, variable knowing the value/category of independent variables
  • OR can be calculated from this for a measure association
45
Q

What are the different types of regression tests for each type of data?

A

nominal -> logistic regression

ordinal -> multinominal logistic regression

interval -> linear regression

46
Q

For nominal data what tests can be run for 2 groups of independent data?

A

(Pearson’s) chi squared

47
Q

For nominal data, what test can be run for more than three groups of independent data?

A

chi squared test of independence

48
Q

For nominal data, what test can be run for more than or equal to two groups with expected cell count of less than five?

A

-Fisher’s Exact test

49
Q

What are the assumptions for a chi squared test?

A
  • usual chi square distribution for nominal type data

- no cell with expected count of less than 5

50
Q

What are the two hypotheses one makes before starting a study?

A

Null hypothesis: states that there will be no true difference between groups compared

Alternate hypothesis: there will be a difference between groups

51
Q

After a chi squared test is conducted in three independent groups to determine a difference between the groups. What test do you use to figure out where the difference lies?

A
  • post hoc test

- multiple chi squared tests introduce increase in type 1 error

52
Q

What is the Bonferroni test of inequality?

A

-adjusts the p value for # of comparisons being made, conservative

53
Q

Test for nominal 2 groups of paired/related data?

A

McNemar test

54
Q

Test for nominal 3 or more of paired/related data?

A

-Cochran test

55
Q

What are the key words for paired/related data?

A
  • pre vs post
  • before vs after
  • baseline vs end
56
Q

Test for ordinal 2 groups of independent data?

A

Mann-Whitney test

57
Q

Test for ordinal three or more groups of independent data?

A

-Kruskal-Wallis test
+compares the median values between groups
+use post hoc if group comparison is significant

58
Q

Test for ordinal 2 groups of paired/related data?

A

-Wilcoxon Signed Rank test

59
Q

Test for ordinal 3 or more paired/related data?

A

-Friedman test

60
Q

What are the three post hoc tests for ordinal data? What are the differences?

A

-Student-Newman-Keul test
+compares all pairwise comparisons possible
+all groups must be equal in size
-Dunnett test
+compares all pairwise comparisons against a single control
+all groups must be equal in size
-Dunn test
+compares all pairwise comparisons possible
+useful when all groups are NOT of equal size

61
Q

Test for interval 2 groups of independent data?

A

-student t-test

62
Q

Test for interval three+ groups of independent data?

A

-ANOVA
+compares against a single dependent variable
-MANOVA
+compares against multiple DVs

63
Q

What test would you run for interval data with 3+ groups of independent data with confounders?

A

-ANCOVA
+single DV
-MANCOVA
+multiple DVs

64
Q

Are student student t-test a ANOVA interchangeable?

A

yes when comparing two groups

65
Q

Test for interval 2 groups of paired/related data?

A

-paired t-test

66
Q

Test for interval 3+ groups of paired/related data?

A
  • repeated measures ANOVA

- repeated measures MANOVA

67
Q

Post hoc test for 3+ group comparisons in interval data?

A

-Student-Newman-Keul test
-Dunnett test
-Dunn test
-Tukey or Scheffe test
+compare all pairwise comparisons possible
+all groups equal in size

68
Q

What is the Kappa statistic?

A

-agreement between evaluators (consistency of decisions and determinations)

69
Q

What are the different interpretations for Kappa?

A

+1= observers perfectly classify everyone the same way

0= there is no relationship at all between the observers’ classifications, above the agreement that would be expected by chance

-1= the observers classify everyone exactly the opposite of each other

70
Q

What is the National Clinical Trials number?

A

-a # assigned by clinicaltrials.gov once research protocol is submitted prior to study initiation

71
Q

What is the purpose of the NCT#?

A

-purpose was to reduce publication bias

72
Q

What do most clinicians want to know how to do with research papers?

A
  • delineate the differences in study designs and to determine which design is most appropriate for a given research question
  • evaluate how study design might impact results
  • determine strengths and weaknesses for various study designs
  • determine what elements can influence study results (biases and confounders)
  • determine the most appropriate statistical test for desired comparisons, based on research question and variable measurements
  • determine if author’s conclusions are sound and based on actual study results
73
Q

What is one folly in trying to assess research?

A

-authors may neglect to provide lucid and complete descriptions of critical, necessary information

74
Q

What do healthcare professionals use to assess published medical literature now?

A

CHECKLISTS

75
Q

Where can you go to get checklists?

A

-equator network

76
Q

What checklists are utilized for interventional studies?

A

-consort (consolidated standards of reporting trials)
+non-inferiority and equivalence trial
+cluster trials
+pragmatic trials
-prisma (systematic reviews of multiple randomized trials)

77
Q

What checklist is utilized for observational studies?

A

-strobe (cohort, case-control, cross-sectional)
+strobe-me
+strega

78
Q

What checklist is used for a non-randomized study?

A

-trend (reporting evaluations with non-randomized designs of behavioral and public health interventions)

79
Q

What is the checklist for tumor marker prognostic studies?

A

-remark (tumor marker prognostic studies)

80
Q

Checklist for genetic risk prediction studies?

A

-grips(genetic risk prediction studies)

81
Q

Checklist for diagnostic studies?

A
  • stard

- quadas-2 (systematic reviews of multiple diagnostic studies)

Epidemiology- Erin (3 decks)

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