Class 11: research 2 Flashcards

1
Q

what is a type 1 error

A

fasle positive - you are preg (man)

When you incorrectly reject a
true null hypothesis.

1 > P

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2
Q

what is a type II error

A

false negative - you are not preg (women)

Failing to reject a false null
hypothesis.

II > N

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3
Q

what are Likelihood Ratios used for

A

To determine how much a test result changes the probability of having a disease.

Combine both sensitivity and specificity into a single measure, making them more comprehensive.

Likelihood Ratios help clinicians make better diagnostic decisions.

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4
Q

Positive Likelihood Ratio (LR+) - what does a higher LR+ indicate

A

positive test result is more likely to be
seen in someone with the disease.

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5
Q

Positive Likelihood Ratio (LR+) - is the test more likely to rule in or rule out the condition

A

ruling in

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6
Q

Positive Likelihood Ratio (LR+) - what is a large shift in probability

A

> 10 = large shift in probability

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7
Q

Negative Likelihood Ratio (LR-) - what does a low LR- indicate

A

better the test is at ruling out the condition.

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8
Q

Negative Likelihood Ratio (LR-) - what is a large shift in prob

A

<0.1 = large shift in probability away from a diagnosis.

Values between 0.1 and 10 are not a large shift and not definitive
in ruling in or out.

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9
Q

what does a p-value of 0.8 indicate

A

indicates 8% probability that the difference
between the groups is due to chance

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10
Q

what is Alpha value:

A

Predefined threshold that determines if your result is statistically significant

Level of statistical significance, usually set before the study

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11
Q

what is a alpha value normally set to

A

0.05 à allowing 5% chance of error

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12
Q

in term of p and alpha values what must be true for a study to be statistically significant

A

p value must be lower or
equal to alpha level

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13
Q

Parametric - distribution

A

equal bell curve

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14
Q

Parametric - sample

A

randomized

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15
Q

Parametric - quantitative or qualitative

A

quantitative

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16
Q

Non-Parametric - distribution

A

non bell shaped -skewed curve

unequal distribution

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17
Q

Non-Parametric - quantitative or qualitative

A

qualitative

love

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18
Q

what is more powerful Non-Parametric or Parametric

A

Parametric

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19
Q

what are the different type of Parametric tests

A

t-test

Analysis of Variance (ANOVA):

ANCOVA:

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20
Q

what are the different types of Non-Parametric Tests

A

Chi square test

Mann Whitney U test

Kruskal Wallis test

21
Q

what is Correlation

A

Describes the strength and direction of a relationship between two variables.

22
Q

what is Positive Correlation

A

Both variables show same direction of
change.

Ex. Number of hours studying and NPTE scores

23
Q

what is Negative Correlation

A

One variable increases while the other
decreases.

Ex. Duration of exercise and body weight

24
Q

Correlation - high

A

> .76 to 1.00

25
Correlation - mod
.51 to .75
26
Correlation - fair
.26 to .50
27
Correlation - low
0.00 to .25
28
what is Regression
Regression examines how changes in the independent variables (predictors) are associated with changes in the dependent variable (outcome)
29
what is a strong regression
R square > 0.5 indicates strong association between variables
30
what is the difference in correlation and regression
* Correlation > measurement of strength/direction of relationship * Regression > prediction
31
Compares mean between 2 independent groups: P and NP
P: Independent T-test NP: Mann-Whitney U-test
32
Compares mean between 2 dependent groups: P and NP
P: Paired T-test NP: Wilcoxon Signed Rank test
33
Compares mean between 3 or more independent groups: P and NP
P: ANOVA NP: Kruskal Wallis test
34
Quantifies association between 2 variables: P and NP
P: Pearson product correlation NP: Spearman rho correlation
35
what is the sensitivity formula
TP/TP+FN
36
what is the specificity formula
TN/TN+FP
37
what is the formula for LR+
sn/1-sp
38
what is the formula for LR-
1-sn/SP
39
when is 1 tailed vs 2 tailed used
1 tailed - you know the direction of the hypothesis - you know this medicine works really well 2 tailed - do not know the direction of the hypothesis
40
what is the differnce between one way anova and two way anova
one way: only looking at one factor - age two way: looking at two factors - age and activty
41
what is repeated measure anova
looking at the same group of indivduals over a period of time
42
what makes ancova different
the present of a co-varient
43
what is the difference between paired and independent t-tests
paired - same group of indivduals at the different time points independent - looking at the difference between two groups of indviduals
44
chi squared test is used for what kind of data
nominal - unequal, mutally exclusive groups
45
manny white U -test
T independent test 2 independent groups unequal ordinal data
46
kruskal wallis tes
anova 3 more groups unequal ordinal
47
over what number indicates a strong correlation
>.75
48
what is the correlation and regression coefficient
R = regression r = correlation
49
R square > 0.5 indicates what
strong association between variables