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Medical Research > Glossary Terms > Flashcards

Glossary Terms Flashcards

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USMLE® Step 1 flashcards
1
Q

hypothesis stating that there is no difference between the study groups

A

null hypothesis

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2
Q

probability that a difference between study groups would have occurred if the null hypothesis was true

A

P value

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3
Q

range in which we can be approximately 95% certain that the population value lies

A

95% confidence interval

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4
Q

When the null hypothesis is incorrectly rejected; a difference between groups is statistically significant although a clinically important difference exists
alpha error; false positive

A

Type I Error

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5
Q

When the null hypothesis is incorrectly accepted; a difference between groups is not statistically significant although a clinically important difference exists

A

Type II Error

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6
Q

number of new cases of a condition that develop in a population during a defined time period (cases/year)

A

incidence

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7
Q

total number of people in a population with a condition during a given point in time (cases at birth)

A

prevalence

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8
Q

statistic used to test whether the rate of an outcome is significant;y different between two or more exposure groups.
This test provides a probability that the outcome and exposure are independent

A

Chi-Square test

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9
Q

statistic used to test whether there is a linear trend for an outcome to increase or decrease over the range of an ordered categorial exposure variable

A

Chi-Square test for trend

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10
Q

the probability of an event or outcome occuring - such as infection, death, cure

A

risk

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11
Q

ratio of the probability of the outcome occurring in the exposed group, divided by the probability of the outcome occurring in the non-exposed group

A

relative risk

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12
Q

the probability of an event (p) occurring divided by the probability of that event not occurring (1-p)

A

odds

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13
Q

radio of the odds of the outcome occuring in one group divided by the odds of the outcome occurring in another group

A

odds ratio

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14
Q

initial trial of a new treatment to assess SAFETY and feasibility in a small group of volunteers who do not have the disease or patients with symptoms

A

Phase I Trial

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15
Q

clinical trial to measure EFFICACY - the effect of treatment under ideal conditions in patients with the disease

A

Phase II Trial

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16
Q

large randomized control trial or multi-center study to measure EFFECTIVENESS in the community - the effect of treatment in GENERAL CLINICAL PRACTICE

A

Phase III Trial

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17
Q

POST MARKETING survery to measure rare adverse events

A

Phase IV Surveillance

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18
Q

All participants are analyzed in the group to which they were allocated, regardless or subsequent events such as non-complicance or withdrawal from the study. This provides a conservative estimate of treatment effect that is not influenced by cofounders

A

Intention-to-Treat analysis

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19
Q

only participants with final study outcomes are included in the data analysis but participants are maintained in the group to which they were allocated - results may be influenced by bias and cofounders

A

Available-case analysis

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20
Q

participants are re-grouped according to the treatment they actually received, irrespective to te treatment to which they were allocated - by using this method there is no control of cofounders

A

treatment-received-analysis

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21
Q

number of people who need to receive a new treatment to prevent one adverse event from occurring

A

number-needed-to-treat (NNT)

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22
Q

frequency of the outcome in the control (current best practice treatment or placebo) group

A

control event rate (CER)

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23
Q

frequency of the outcome in the experimental (new treatment) group

A

experimental event rate (EER)

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24
Q

the reduction in risk (probability of the outcome) that is conferred by the new treatment

A

absolute risk reduction (ARR)

25
Q

the outcome measurement in a study - the variable of interest such as the primary illness or disease status indicator

A

outcome variable

26
Q

characteristic that is hypothesized to influence the outcome variable - in clinical studies this is often the group to which patients have been randomized. In cross sectional and cohort studies these are often exposure variables

A

explanatory variables

27
Q

stats used when the outcome measurement has a distribution that is approximately normal

A

parametric statistics

28
Q

squared term that describes the total variation in the sample

A

variance

29
Q

meausre of variability that describes how far the data spreads on either side of the central mean value. It is the square root of the variance and therefore is in the same units as the data values

A

standard deviation (SD)

30
Q

data points at the extremities of the range or separated from the normal range of data values. Data points are MORE THAN 3 SD from the mean are usually considered this

A

outlier

31
Q

calculated by dividing a mean value by its SE - gives a number from which the probability of the event occurring is estimated from a t-distribution

A

T-value

32
Q

this is closely related to a normal distribution but depends on the number of cases in the sample

A

T-distribution

33
Q

test to measure whether a continuous outcome variable with a normal distribution is significantly different between two groups - example between male or female or between an intervention and a control group

A

independent samples T-test

34
Q

test used to compare the mean values of two independent samples using a normal distribution - only used when the sample size is very large or the mean and SD of the population are known

A

unpaired Z-test

35
Q

distance between two mean values, described in units of their SD that describes the relative magniftute of the difference between two groups

A

Effect size

36
Q

Pearson’s correlation coefficient that measures the strength of a linear relationship between two continuous normally distributed variables

A

R value

37
Q

coefficient of determination is equal to the squared correlation coefficient and provides an estimate of the percent of variation in one variable that is explained by the other variable

A

R ^2

38
Q

sample taken from a population in which all people have an equal chance of being selected

A

random selection

39
Q

range of values in which the majority of people in a population expected to lie

A

normal values

40
Q

distance between an observed value and its predicted value - in this case the value predicted by the regression line

A

residuals

41
Q

regression line through a set of data points calculated to minimie the sums of squared residuals

A

line of best fit

42
Q

study which is conducted to measure rates of disease in a population or to meausre associations between exposures (risk factors) and disease

A

observational study

43
Q

study conducted to test the effect of a treatment or intervention

A

experimental study

44
Q

study which is conducted to measure whether a new treatment is superior or equivalent to no treatment or an existing treatment - participants are randomly allocated to the study groups

A

randomized controlled trial

45
Q

study in which participants receive two or more treatments given consecutively usually in random order. The response to the first treatment can be contrasted with the response to the second treatment in the same participants

A

cross-over trial

46
Q

test to measure whether the means of two related continuous meausres are different from one another, typically measurements taken from the same participants on 2 occasions

A

Paired T-test

47
Q

outcome of interest which is typically death but can be non-fatal or favorable outcome such as discharge from hospital

A

event

48
Q

used to describe participants who withdraw from the study or who do not experience the outcome of interest

A

censored observations

49
Q

statistic used to compare the event rate over time between two or more study groups - also called long-rank test

A

Kaplan-Meier statistic

50
Q

risk of the event in a study group divided by the risk of the event in a reference group

A

Hazard ratio

51
Q

test used to confirm a disease in people who present with signs or symptoms

A

diagnostic test

52
Q

test regarded as the most accurate method available for classifying people as disease positive or negative

A

gold standard

53
Q

probability of a positive test in a person with the disease compared to the probaility of a positive test in a person without disease

A

likelihood ratio

54
Q

proportion of test-negative people who do not have the disease

A

negative predictive value

55
Q

proportion of test-positive people who have the disease

A

positive predictive value

56
Q

test used for early identification of disease in a population without symptoms

A

screening test

57
Q

proportion of disease positive people who are test-positive

A

sensitivity

58
Q

proportion of disease-negative people who are test-negative

A

specificity

59
Q

meausre of precision with which the mena value has been measured

A

Standard Error (SE)

Medical Research (2 decks)

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