Terminology Flashcards

1
Q

Descriptive studies

A

Record activities, observations or events
Rare to provide info to evaluate new treatments

Eg case reports, case studies, population studies/cross-sectional studies

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2
Q

Case series

A

Tracks patients with a known exposure or similar treatments, or examines their medical records for exposure and outcome

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3
Q

Cross-sectional studies

A

Information about a population at a slice in time

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4
Q

Explanatory studies

A

Seek to find info about the causes of illness or the effectiveness of treatments

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5
Q

Observational studies

A

Studies of the course of disease and health events, then the results are used to reach conclusions

Types:
Identify individuals known to have a disease or problem, then looking for factors in the past that might have led to the problem
Dealing with individuals who don’t have a problem, but following them over time to study characteristics that might be related to development of a disease or problem.

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6
Q

Case control study

A

Individuals who ar known to have a disease or problem of interest and compares to others who aren’t affected

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7
Q

Cohort study

A

Selecting a starting point and collecting information as you go
Essentially a follow up study
Look at the causes of disease - identifying individuals with some sort of exposure and following them over time to see what happens to them
Provides info about the course and prognosis of diseases
Nature of group influences generalizability

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8
Q

Interventional studies

A

Specifically examine the effect that some intervention might have on patients

Eg social support, New med, new procedure to treat illness

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9
Q

Evidence level rankings

A

1 or A:RCT
II-I: CT but not random
II-2 or B: cohort. Or case-control studies
II-3. Or C: case series
III or D: expert opinion or descriptive studies

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10
Q

Nominal data

A

Categorical. Data
Given names
No level of severity, just different grouping. Eg blood type

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11
Q

Ordinal data

A

Categorical
Describe a progression. Of something
Observation put in order
Eg cancer stage

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12
Q

Binary data

A

Yes/no

Dead//alive

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13
Q

Continuous variables

A

Any value in a range

Height, weight, etc

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14
Q

Discrete data

A

Can only take certain values

Doses given,, completed weeks of gestation

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15
Q

Qualitative

A

Descriptions

Describe qualities of the. Information

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16
Q

Quantitative.

A

Can. Be measured with a numerical value.

17
Q

Mode

A

Most common value within a group

18
Q

Standard deviation

A

Spread of data
Mean of the mean
Tells how tightly all the various examples are clustered around the mean in a set of data

19
Q

Confidence interval

A

Upper and lower values that will include 95% of data from a sample

20
Q

Probability distribution

A

Way of showing the chances that any value will be found in a population
Eg normal distribution

21
Q

Null hypothesis

A

No difference between two interventions

22
Q

Alternative hypothesis

A

Real difference in the effectiveness of interventions

23
Q

Statistical significance

A

%5% chance (1:20) that the difference found between two interventions in the study are due to random chance
95% certainty that the difference is real

24
Q

P-value

A

Probability that the alternative hypothesis is correct

25
Q

Chi squared probability test

A

The sum of the squared difference between observed and expected data, divided by the expected data in all possible categories
Chi Squared = (o-e)^2/e

Used with independent groups

26
Q

Paired t-test

A

Used to determine whether the mean difference between two sets of observations is zero OR
Used to compare 2 population means where you have two samples in which observations in one sample can be paired with observations in the other sample
Used to determine if there is a sig diff between mean in two groups
Need the mean difference, standard deviation of each group, and the number of data values of each group

Used in case-control studies or repeats-measures designs
Eg before and after observations on the same subjects
A comparison of 2 different methods of measurement or two different treatments where the measurement/treatments are applied to the same subjects

27
Q

Absolute risk

A

Probability that a certain event will occur in a specified population

28
Q

Absolute risk difference/risk reduction

A

Difference in risk for an event or outcome between an exposed population and an unexposed population

29
Q

Relative risk

A

Used in RCT and cohort studies

Ratio of two risks (or probabilities), usually the risk of an event or disease in an exposed group and the risk in an unexposed group

30
Q

Odds ratio

A

Ratio of two mutually-exclusive events

Eg have pre-eclampsia, do not have pre-eclampsia

31
Q

Type 1 error

A

Rejecting the null hypothesis when it is true

32
Q

Type II error

A

Not rejecting a null hypothesis when the alternative hypothesis is the true state of nature

-usually when sample size too small

33
Q

Unpaired t test

A

Compares two independent samples drawn from the same population

Mann-Whitney U test

34
Q

F test

A

One way analysis of variance using total sum of squares

Compare three or more sets of observations on a single sample

35
Q

Pearson’s r

A

Product moment correlation coefficient

Assesses the strength of the the straight line association between two continuous variables

36
Q

Multiple regression by least squares method

A

Describes the numerical relation between a dependent variable and several predictor variables (covariates)

37
Q

Incidence

A

Number of new cases of a condition or disease in a given population over a given time