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Biostatistics > Exam 3 > Flashcards

Exam 3 Flashcards

1
Q

Probability

A

Deals with the relative likelihood that a certain event will or will not occur, relative to some other events

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2
Q

Probability is a synonym of

A

proportion

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3
Q

Occurrence of an event is just as likely as it is unlikely at probability

A

0.5

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4
Q

Probability values assigned to each experimental outcome must be between

A

0 and 1

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5
Q

The sum of all experimental outcome probabilities must be

A

1

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6
Q

Outcome space/sample space

A

All possible outcomes.

Mutually exclusive and exhaustive

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7
Q

Complement of an event

A

The complementary event A refers to the event consisting of all sample points that are not in A

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8
Q

Probability of intersect (joint)

A

Probability of both A and B occurring at the same time

Two events A and B that are not mutually exclusive

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9
Q

Probability of conjoint (union)

A

The probability of either A or B occurring

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10
Q

Conditional probability

A

p(A|B)

The probability of an outcome, given that a certain value is already known for a second variable.

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11
Q

Non-parametric Chi-square test

A

Involves discrete variables (categorical data). It does not require assumptions of homogeneity or normality
Nominal (yes/no) data
Evaluating the difference between the frequencies actually observed in the sample

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12
Q

Df of chi squared

A

n-1

(n-1)(r-1) for test of independence

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13
Q

Chi squared test, if the calculated value is less than the critical value what happens?

A

We fail to reject the null hypothesis.

No change

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14
Q

Chi square test of independence

A

To determine if the two discrete variables are independent of each other or if an association exists.
Attempting to find out if one variable predicts another variable.
Data is displayed in a contingency table of rows and columns

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15
Q

Chi square, what do we do when the calculated statistic is greater than the critical value?

A

Reject the null hypothesis

There is a significant difference

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16
Q

Assumptions of chi square test of independence

A

There must be at least one observation in every cell, no empty cells
The expected value for each cell must equal or be larger than 5

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17
Q

Yates Chi Square for conservative estimation

A

Used in certain situations when testing for independence on a contingency table.
Produces a smaller numerator and a more conservative estimate for the chi square statistic; harder to reject null

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18
Q

Fishers Exact Test for less data

A

Used when data for a chi-square test of independence is reduced to 2x2 and the expected values are still too small or have a zero in the cell
Can be non-parametric median test or probability for multiple tests

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19
Q

McNemars Test

A

Will be used to evaluate the relationship or independence of paired discrete variables (like paired T test)

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20
Q

When to use OR vs RR?

A 
OR are more commonly reported incase control, cohort studies and clinical trials
OR can be an estimate of RR
If the outcome of interest is rare, OR=RR
Either overestimate (OR>1) or underestimate (OR<1)
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21
Q

NNT

A

The number of patients needed to treat with the specified therapy in order for one patient to benefit.
Inverse of ARR

22
Q

Logistic regression

A

An extension of multiple regression methods for use where the dependent variable is dichotomous (dead/alive)
Determines the predicted probability of the outcome based on the combo of predictor values

23
Q

Simple logistic regression

A

Logistic regression with one independent and one dichotomous dependent variable

24
Q

How do you solve the problem of probabilities not being linear?

A

Transformation to convert into a linear expression

25
Q

How do you transform a probability into a linear expression?

A
  1. ) Convert probability to odds

2. ) Make natural log of odds

26
Q

b1 regular regression

A

For a one-unit change in x we expect an average change in Y of b units, holding all other variables constant

27
Q

b1 logistic regression

A

For a one unit change in x, we expect on average that the predicted odds will change by a multiplicative factor of e^b1 holding all else constant

28
Q

Cox proportional hazard regression

A

Accounts for the effects of predictor continuous and discrete variables on the dependent variable, which can include censored time-until-event
To compare survival in two or more levels of an independent variable adjusting for multiple covariates

29
Q

What is research?

A

A systematic approach to find answers to questions

30
Q

Applied vs Basic research

A

Applied- solving problems

Basic- understanding problems

31
Q

Cross-sectional study

A

It takes place in a single point in time

32
Q

Longitudinal study

A

Takes place over time. You have at least 2 or more waves

33
Q

Exploratory Research

A

Invesitgating or discovering something that is previously unknown
Zika, Ebola , swine flu

34
Q

Descriptive Research

A

A systematic attempt to symbolize the obvious relationships that are found among the natural phenomena under study
Association between variables, frequency of occurrence

35
Q

Explanatory research

A

To explain (show causal relations between variables) and predict relations
Discovers the answer to the question
Reveals gaps in our understanding

36
Q

Research problem

A

A question demanding a settlement
Expresses a relationship between 2 or more variables, usually in the form of a question, should imply a method of empirical testing

37
Q

Research hypothesis

A

A conjectural statement, a tentative proposition about the relation between two or more variables. It is a prediction from theory under test

38
Q

Bias of systematic error

A

Causes some type of constant error in the measurement with a system

39
Q

Bias of random errors

A

Chance errors

Unpredictable and will vary in sign (+ or -)

40
Q

Selection bias

A

Certain characteristics make potential observations more or less likely to be included in the study
It occurs when confounding factors are unevenly distributed between experimental and control groups.
Also called cherry picking

41
Q

Funding bias

A

It is possible that there is a different quality of research between industry funding and trials without external funding.
Financial interest may bias interpretation

42
Q

Publication bias

A

A selective publication of trials with certain results may lead to an exaggeration of effects

43
Q

Reliability

A

A collection of factors and judgments that, when taken together, are a measure of reproducibility. The consistency of measures

44
Q

Validity

A

Refers to the fact that the data represents a true measurement
A valid piece of data describes or measures what it is suppose to represent

45
Q

Conclusion validity

A

Is there a relationship between the cause and effect?

Means conclusion we reach about our relationship is reasonable.

46
Q

Internal validity

A

Is the relationship causal?

Example- whether the program causes the outcome

47
Q

Construct validity

A

Can we generalize to constructs?
If there is a causal relationship in a study, did you measure the outcomes you wanted to measure?
Can you claim that the research program reflected your intended construct of the program?

48
Q

External validity

A

Can we generalize to other persons, places, times?

49
Q

Descriptive data analysis

A

Range, mean, SD, percentage, CI

50
Q

Inferential statistics

A

Parametric- tTest, ANOVA

Non-parametric- chi square, logistic regression

Biostatistics (2 decks)

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