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Orthopedic Surgery Ultimate > Research and Stats > Flashcards

Research and Stats Flashcards

1
Q

Define positive predictive value

A

probability a patient with a positive test actually has a disease

PPV = TP / (TP + FP)

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2
Q

Define variance

A

an estimate of the variability of each individual data point from the mean

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3
Q

define effect size

A

magnitude of difference in means between two groups

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4
Q

case control studies (retrospective) typically generate what statistical measure?

A

odds ratio

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5
Q

Define Type I error (alpha)

A

null hypothesis is rejected even though it is true

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6
Q

negative likelihood ratio: define and formula

A

how the likelihood of a disease is changed by a negative test result

(1-sensitivity)/specificty

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7
Q

what is a type II error?

A

beta.

false negative

detecting no difference when there is one

accepting a null hypothesis wrongly

typically set at 0.8

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8
Q

Describe Post-test odds of disease

A

post-test probability = (pretest probabililty) X (likelihood ratio)

  • likelihood ratio = sensitivity / (1 - specificity)
  • pre-test odds = pre-test probability / (1 - pre-test probability)

post-test probability = post-test odds / (post-test odds + 1)

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9
Q

What does positive predictive value depend on?

A

prevalence of a disease

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10
Q

Define effect size

A

magnitude of the difference in the means of the control and experimental groups in a study with respect to the pooled standard deviation

Effect sizes are normally used for continuous variables in contrast to relative risk reduction which is used for dichotomous variables

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11
Q

NNT formula and definition

A

NNT=1/ARR

number needed to treat to get one additional favourable outcome

alternatively, ARR=1/NNT

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12
Q

Define negative predictive value

A

probability a patient with a negative test actually has no disease

= TN / (FN + TN)

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13
Q

a highly ____ test with a (neg/pos) result can rule (in/out) the outcome of interest

A

SENSITIVE tests with NEGATIVE results rule OUT the outcome

“SNNOUT”

SPECIFIC tests with POSITIVE results rule IN the outcome

“SPPIN”

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14
Q

define incidence

A

number of newly reported cases of a disease during a given time period

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15
Q

What test do you use to compare 2 independent means from numeric data?

A

t-test

numeric data = t-test

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16
Q

How do you determine absolute risk reduction?

A

From NNT

NNT = 1 / ARR

ARR = 1 / NNT

or

ARR = (risk in control group - risk in experimental group)

*this was on a previous exam

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17
Q

test for comparing means of 3 or more continuous dependent variables

(each with categorical independent variables)

A

ANOVA

this is essentially a t-test for 3 or more groups

ANOVA on 2 groups will give the same result as a t-test

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18
Q

Define Type II error

A

Beta error

a false negative difference that can occur by:

  • detecting no difference when there is a difference
  • accepting a null hypothesis when it is false and should be rejected
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19
Q

sensitivity formula

A

TP/(TP+FN)

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20
Q

Student t-test

A

used to compare means of continuous data that is normally distributed

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21
Q

What does a relative risk > 1 mean?

A

incidence of the outcome is greater in the exposed/treated group

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22
Q

test to see if two continuous variables are related or not

A

linear regression

e.g. comparing age to BP

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23
Q

Kaplan-Meier equation (in laymans terms)

A

The number of failures / total number still being followed

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24
Q

statistical tool in meta-analyses to detect publication bias

A

funnel plot

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25
describe negative likelihood ratio
describe how the likelihood of a disease is changed by a negative test result negative likelihood ratio = (1 - sensitivity) / specificity
26
define relative risk and give formula
* risk of developing disease with exposure compaerd to risk of developing disease without exposure * risk of disease with exposure=(have exposure and disease)/(all with exposure) * risk of disease without exposure=(no exposure but have disease)/(all without exposure) * RR=(risk of disease with exposure)/(risk of disease without exposure)
27
Mann-Whitney or Wilcoxon rank sum tests
comparing means of non-continuous data
28
Describe Relative risk
risk of developing disease for people with known exposure compared to risk of developing disease for people *without* known exposure
29
incidence definition
number of new cases in a given time period
30
How do you compare categorical data?
chi-square test
31
What is the fisher exact test used for?
Comparing proportional or categorical data when sample sizes are small or number of occurences in a group is low
32
positive likelihood ratio; formula and definition
sensitivity/(1-specificity) how likelihood of a disease is changed by a positive test result
33
What does blinding do?
minimizes observer bias
34
Define positive likelihood ratio
describes how the likelihood of a disease is changed by a positive test result positive likelihood ratio = sensitivity / (1-specificity)
35
define likelihood ratio
likelihood a result is expected in someone with the disease compared to likelihood the result is expected in a normal person
36
An underpowered study is prone to what type of statistical error?
Type II error (beta)
37
Define Number needed to treat
number of patients that must be treated in order to achieve one additional favourable outcome NNT = 1 / absolute risk reduction
38
What does randomization do?
Decreases selection bias
39
What test do you use to compare 2 means with non-parametric (non-normal) data?
mann-whitney or wilcoxon sum rank test
40
Name 2 ways of minimizing the effects of chance in study design
Having an adequate sample size based on power calculations The use of appropriate levels of significance in hypothesis testing
41
What is an independent risk factor for postop MI post total joint arthroplasty? What can you do to prevent it?
Hypertension Administration of beta blockers for 7 days decreases risk of cardiac ischaemic events and in-hopsital deaths
42
What is a funnel plot?
Is a simple scatter plot of the intervention effect estimates from individual studies against some measure of each study’s size or precision I**s used to detect publication bias in meta-analyses**
43
Sensitivity
probability that test results will be positive in patients *with* the disease = TP / (TP + FN) = people with the disease who tested positive / everyone with the disease
44
What test do you use to compare 2 means with normal (parametric) data
Student t-test
45
Define false negative
Patients with the disease but have a negative result False negative rate = FN / (TP + FN) = FN / everyone who is positive
46
Describe Odds ratio
probability of having a risk factor if one has a disease obtained from case control studies (retrospective studies) OR = (odds of developing disease in exposed patients) / (odds of developing disease in unexposed patients)
47
test to show how a change in a variable (categorical or continuous) affects another variable (categorical, dichotomous)
logistic regression e.g. seeing if body weight is related to presence or absence of lung cancer
48
define power (wrt stats) and give the formula
estimate of the probability a study can detect a true effect of the intervention power=1-beta
49
prevalence definition
number of cases of something at a single point in time for a given population
50
Specificity
probability that the test result will be negative in patients *without* the disease = TN / (FP + TN) = people without disease who tested negative / everyone who *doesn't* have the disease
51
What does PPV depend on?
prevalence of a disease
52
In a screening test, you want it to be highly \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_
Sensitive
53
PPV formula
TP/(FP+TP)
54
What kind of studies do you get odds ratio's from?
retrospective studies (case-control) b/c it is the proability of having a risk factor given a person has the disease
55
Define False positive
patients without the disease who have a positive test result false positive rate = false positives / (FP + TN) = FP / everyone who is negative
56
Where do you get a relative risk ratio from?
Cohort studies b/c you need incidence to calculate it
57
test for comparing means of 2 continuous dependent variables (each with categorical independent variables)
student t-test e.g. comparing average BP (the continuous dependent variable) in a group of smokers vs. nonsmokers (smoking is the categorial independent variable)
58
ANOVA
compare means of 3 or more independnet groups in normally distributed data
59
test to compare 2 or more categorial dependent variables (each with categorial independent variables)
chi-square e.g. comparing # of ppl with ecoli who ate burgers with #ppl with ecoli who didnt eat burgers (# of ppl is categorical) i.e. if you can fit your data into a 2x2 table, use a chi-square test (ate burger, didnt eat burger vs. ecoli, no ecoli)
60
specificity formula
TN/(FP+TN)
61
In a Kaplan-Meier analysis, what do you do with the patients that are lost to followup
Exclude them from the study They are assumed to be similar to the patients still in the study
62
define odds ratio and give formula
probabilyt of having a risk factor given you already have the disease OR=(odds of getting disease when exposed)/(odds of getting disease if unexposed)
63
What is a bonferroni correction?
post-hoc statistical correction made to P values when several dependent or independent statistical tests are being performe dsimultaneously on a single data set
64
What do cross-sectional studies aim to achieve?
Identify the prevalence of a condition
65
what is a type I error?
alpha. false positive rejecting null hypothesis when it's true we typically set this at 0.05
66
Describe a confidence interval
The Interval that will include a specific parameter of interest, if the experiement is repeated
67
Define alpha level?
probability of a type I error occuring (reject null when its true) typically set at 0.05
68
What studies are generally reported as an odds-ratio?
Case-control study
69
t-tests mann-whitney sum rank tests chi quare test fischer exact test are all types of what?
Statistical inference used to test specific hypotheses about associations or differences among groups of subjects/sample data
70
test to compare two categorical variables with small sample sizes
fisher exact test (similar idea to chi-square but with small sample sizes) for samples \<5 or total of all cells \<50 (in your 2x2 table) - see chi-square card
71
What does NPV depend on?
prevalence of disease
72
Define Power (stats)
an estimate of the probability a study will be able to detect a true effect of the intervention power = 1 - (probability of a type II, or beta, error)
73
define prevalence
total number of cases of a disease present in a location at any time point
74
what is a bonferroni correction?
post-hoc statistical correction to P-values when several tests are performed simultaneously on a single data set
75
What studies are generally reported as relative risk?
Cohort studies
76
define Likelihood ratio
likelihood that a given test result would be epxected in a patient with the target disease compared to likelihood that the same result would be expected in a patient without the target disease
77
NPV formula
TN/(FN+TN)
78
What does matching in a study design do?
Minimizes confounders

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