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LECOM Biostatistics 2022 > Important Definitions > Flashcards

Important Definitions Flashcards

1
Q

What makes a good hypothesis?

A

Valid data gathering and no fishing expeditions

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2
Q

What are the four steps of hypothesis testing?

A
  1. Make hypothesis
  2. Set criteria for decision
  3. Gather data and conduct statistical analysis
  4. Make decisions -> accept H0 or reject HA
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3
Q

What is the Null Hypothesis (H0)?

A

No difference
- All samples from same population
- Observed difference due to chance (random sampling)

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4
Q

What is the Alternative Hypothesis?

A

At least one sample from a different population
- Difference not due to chance

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5
Q

All statistics are based on…

A

Probability

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6
Q

What is our main goal in hypothesis testing?

A

Rejecting the null

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7
Q

If alpha < our result, then…

A

We accept the null

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8
Q

If alpha > our result, then…

A

We reject the null

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9
Q

What does mutually exclusive indicate?

A

Only one event can occur
Ex: heads or tails

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10
Q

What does independent variables indicate?

A

Either event could occur
Ex: roll a 6 on one die and a 6 on the other die

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11
Q

When do we use the additive rule?

A

With a mutually exclusive event

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12
Q

When do we use the multiplicative rule?

A

With an independent probability

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13
Q

What is sampling?

A

Selection of study subjects who will be
measured on some parameter to provide information about population

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14
Q

What are the representative sampling techniques?

A
  • Simple random sampling
  • Systematic sampling
  • Stratified sampling
  • Convenience sampling
  • Multistage sampling
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15
Q

Simple random sampling

A

Each individual has equal chance of being selected
Ex: drawn out of hat

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16
Q

Systematic sampling

A

Select at regular intervals through an ordered list
Ex: interview 3rd patient for one week

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17
Q

Stratified sampling

A

– Separate population into strata based on a Separate population into strata based on a characteristic
–– Randomly select proportion of participants from each stratum
Ex: picking only freshmen, and then select randomly within freshmen

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18
Q

Cluster sampling

A

Population already in strata
* Randomly select groups of strata

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19
Q

Convenience sampling

A

Cold call
* Does not typically represent population

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20
Q

Multistage sampling

A

Combines more than one sampling
Ex: randomly selected PCPs chosen for survey, when answering, second detailed survey sent out to randomly selected sample

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21
Q

What is a qualitative variable?

A

Catergorical: groups, cohorts
Ex: ethnicity, gender, disease status, age group, stage of cancer, pain rating

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22
Q

What is a quantiative variable?

A

Continious: measured quantities
Ex: height, weight, temperature, blood pressure, temperature

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23
Q

What is an independent variable?

A

Input, manipulative

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24
Q

What is an dependent variable?

A

Outcome, response, predicted

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25
Q

What are measures of central tendency?

A

Mean, median, mode

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26
Q

What are measures of dispersion?

A

Range, interquartile range, percentiles
Standard deviations (SEM), max/min, kurtosis, skewness

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27
Q

What does sample size mean?

A

Number of samples in each group
Larger sample sizes tend to have more statistical power

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28
Q

How can we reduce variance?

A

Increase the sample size
Better define our sample populations
Censor outliers

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29
Q

Unimodal distributions

A

Normal and skewed distribution

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30
Q

What is the bell-shaped curve?

A

Gaussian Distribution

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31
Q

What is Gaussian Distribution used for?

A

Continuous variables

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32
Q

What is described of in Gaussian Distribution?

A

Mean, and standard deviation

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33
Q

In a skewed distribution…

A

Mean not equal to median

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34
Q

Positive skew

A

Mean > median > mode

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35
Q

Negative skew

A

Mean < median < mode

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36
Q

What is kurtosis?

A

Peakedness or flatness of frequency distribution

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37
Q

Higher kurtosis means…

A

Variance from infrequent extreme deviations

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38
Q

What is platykurtic?

A

Negative kurtosis

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39
Q

What is leptokurtic?

A

Positive kurtosis

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40
Q

What is a type I (alpha) error?

A

Probability of rejecting null when it is true

41
Q

What is type II (beta) error?

A

Probability of accepting null when it is false

42
Q

What are the rules of categorical data?

A

Data are arranged into catergories
Data are an independent, random sample from the population
Must be positive integer, > 0

43
Q

What do we assume in categorical data?

A

Random sample of the population

44
Q

What are the type of categorical data studies?

A
  1. Cross-sectional: recruit study group and define (at
    least) two categories.
  2. Prospective: recruit groups with some difference
    (risk factors) and follow them.
  3. Retrospective: start with condition and look
    backwards at potential causes.
  4. Experimental: recruit group, manipulate variables
  5. Diagnostic Test: positive + negative results
45
Q

What are the requirements of the student’s t-test?

A
  1. Data is continuous (not categories)
  2. Data is a random sample from the population
46
Q

What are the assumptions of the student’s t-test?

A
  1. Each of the 2 populations being compared is
    normally distributed
  2. Each of the 2 populations should have the same
    variance
47
Q

One sample t-test

A

Compare a group’s mean to a “benchmark” group

48
Q

Independent t-test

A

Compare two independent groups

49
Q

Dependent t-test

A

Compare 2 groups that are somehow related

50
Q

Two-tailed t-test?

A

LECOM students will score significantly different than group X

51
Q

One-tailed t-test?

A

LECOM students will score significantly higher than group X

52
Q

ANOVA stands for…

A

ANalysis Of VAriance

53
Q

What is ANOVA used for?

A

Comparing means of 3 or more groups

54
Q

What are the assumptions of ANOVA?

A

 Independent observations
 Normally distributed data
 Homogeneity of variance [Levene’s Test]

55
Q

What is a post hoc test identify?

A

Specific groups that are different

56
Q

When do you use Tukey post hoc?

A

Compare each group to every other group

57
Q

When do you use Dunnett’s post hoc?

A

Compare all groups to a control group

58
Q

When can you develop a correlation?

A

Both dependent and independent variables are continious

59
Q

What does correlation not imply?

A

Causation

60
Q

What are the detailed criteria for assessing evidence?

A

– Strength
–– Consistency
–– Specificity
–– Temporality
–– Biological gradient
–– Plausibility
–– Coherence
–– Experiment
–– Analogy

61
Q

Strength in Bradford-Hill Criteria is defined as…

A

Larger association is more likely causal effect

62
Q

Consistency in Bradford-Hill Criteria is defined as…

A

Stronger association when same findings observed by
different people and different samples

63
Q

Specificity in Bradford-Hill Criteria is defined as…

A

Specific population (or risk factor) with specific disease
and no other likely explanation

64
Q

Temporality in Bradford-Hill Criteria is defined as…

A

Effect happens after the cause

65
Q

Biological gradient in Bradford-Hill Criteria is defined as…

A

More exposure = greater incidence

66
Q

Plausibility in Bradford-Hill Criteria is defined as…

A

Plausible mechanism between cause and effect helpful

67
Q

Coherence in Bradford-Hill Criteria is defined as…

A

Link between epidemiological and laboratory findings
increases likelihood

68
Q

Experiment in Bradford-Hill Criteria is defined as…

A

“Occasionally it is possible to appeal to experimental
evidence”

69
Q

Analogy in Bradford-Hill Criteria is defined as…

A

Effect of similar factors may be considered

70
Q

Degree of correlation measured by…

A

r

71
Q

…is coefficient of determination

A

Rsquared

72
Q

What is Spearman’s Rank?

A

Nonparametric test for relationship between 2 variables

73
Q

When do we use survival analysis?

A

Used to analyze data in which time until the event is of interest

74
Q

Types of bias

A
  • Selection bias (sampling)
    ** Measurement bias
    –– Hawthorne effect
    ** Experimenter bias
    –– Pygmalion effect
    ** Lead-time bias
    ** Recall bias
    ** Late-look bias
    ** Confounding bias
    ** Design bias
75
Q

What is selection bias?

A

Sample is not representative of population

76
Q

What is measurement bias?

A

Leading question

77
Q

What is the Hawthorne effect?

A

Participant behavior altered by knowing
they are being studied

78
Q

Experimenter bias (Pygmalion effect)

A

Expected results accidently communicated to
participants

79
Q

Lead-time bias

A

False estimate of survival rates

80
Q

Recall bias

A

Participants do not accurately recall events

81
Q

Late-look bias

A

Participants with severe disease less likely to be
identified because they die first

82
Q

Confounding bias

A

A factor in a study is related to co-factor being
examined

83
Q

Design bias

A

Choosing inappropriate study design to answer
question

84
Q

What is incidence?

A

Measure new cases of disease or injury in of disease or injury in population over specified time period

85
Q

What is prevalence?

A

Measure of total number of cases of disease or injury in population over specified time period

86
Q

What is validitiy?

A

Test detects what it was designed to test

87
Q

What is test sensitivity?

A

Proportion of pts with disease where screening test
is positive
Higher sensitivity, better test in finding diseased
pts

88
Q

What is test specificity?

A

Proportion of pts without disease where screening
test is negative
Higher specificity, healthy pts not diagnosed as
diseased

89
Q

Case-control study

A

Find cases and look in the past

90
Q

Cohort study

A

Choose a group and follow

91
Q

What are the advantages/disadvantages?

A
  • AdvantagesAdvantages
    –– Can estimate incidences
    –– Can calculate risks
    –– Exposure precedes disease
    ** DisadvantagesDisadvantages
    –– Rare disease
    –– Slow time from exposure to disease development
    –– Loss to follow-up
    –– More expensive – longitudinal in time
92
Q

What is phase I in clinical trials

A

Small number of healthy volunteers

93
Q

What is phase II in clinical trials?

A

Small # of pts with disease

94
Q

What is phase III in clinical trials?

A

Randomized Control Trial (next)

95
Q

What is phase IV in clinical trials?

A

Surveillance after approval and use

96
Q

What are key elements to RCT?

A

Treatments, outcomes, benefits

97
Q

What is meta-analysis?

A

A quantitative, formal, epidemiological study design used to
systematically assess previous research studies to derive
conclusions about that body of research

98
Q

What are the advantages of meta-analysis?

A

Improve precision, answer questions not posed by individuals studies, settle controversies arising from apparently conflicting studies

99
Q

What are the principles of meta-analysis?

A
  • It is important to clearly state your hypotheses and
    search strategies to decrease bias and heterogeneity
  • Clearly identify patient population, inclusion and
    exclusion criteria, desired outcomes and intervention
    to be studied
  • Make sure you are comparing apples to apples!

LECOM Biostatistics 2022 (4 decks)

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