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IPE - Winter OD2 > Midterm 2 > Flashcards

Midterm 2 Flashcards

1
Q

What is the purpose of t-test?

A

to compare 2 groups of scores
(does not require a large sample size but it does help)

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2
Q

What are the appropriate types of variables for a t-test?

A

Independent variable: dichotomous
Dependent variable: continuous

Null hypothesis: no difference between 2 groups being compared

Alternate hypothesis: 2 groups of scores are different

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3
Q

What is the purpose of an UNPAIRED t-test?

A

when comparing 2 groups of scores, the 2 groups of scores are INDEPENDENT of each other

AKA 2 group t test, 2 sample t test, independent group t test

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4
Q

For an Unpaired t test, you are (adding/subtracting) the average score of one group to the score of another group

A

subtracting

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5
Q

For an unpaired/paired t test, how does t get bigger?

A

get more participants

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6
Q

What are the degrees of freedom of an unpaired t test?

A

N (total number of observations of the study) - 2

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7
Q

What are degrees of freedom used for?

A

t(#) where # = degrees of freedom

It is a statistic that is a shorthand indicating sample size. It tells us the shape of the distribution

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8
Q

If the t test was t(698) what are the degrees of freedom of this example?

A

df = N - 2
698 = N -2
N = 700

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9
Q

How do you get closer to the normal distribution graph with t distribution?

A

obtain MORE observations

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10
Q

What is the critical value of t?

A

the smallest absolute value of t needed for the observations to be within the alpha level of statistical significance

unique for every freedom

You would need the t value to be greater than the critical value to be statistically significant

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11
Q

Ex: If 2 tailed t test t(698) = 0.75 and p = 0.57 and the critical value is 1.96, does this meet critical value? Is it significant?

A

No. 0.75 < 1.96 so does not fall in statistically significance

It is not statistically significant because p > 0.025

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12
Q

What is a paired t-test?

A

when comparing two groups of scores that are related in pairs (AKA matched groups t test, dependent t test)

scores are paired/linked with one another in some way

ex: for every subject, left eye receives the drug and right eye receives placebo, compare dryness of each eye

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13
Q

Paired t test involves (adding/subtracting) 2 values in a pair and then averaging that difference.

A

subtracting

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14
Q

For the degrees of freedom of a paired t test what is the formula?

A

df = N - 1
N (total number of observations)

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15
Q

How does the graph for t distribution look?

A

it is infinite on a graph and NEVER touches the x axis

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16
Q

What is ANOVA?

A

Analysis of Variance

compare average score of 2 or more groups of scores

independent variable: categorical
dependent variable: continuous
(similar to t test but more groups compared)

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17
Q

ANOVA uses what size of groups and what is the statistic called?

A

small # of groups

F statistic

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18
Q

What is F in ANOVA?

A

variation between groups/ variation WITHIN groups

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19
Q

How is variation measured?

A

mean squares (MS)

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20
Q

What does variation between groups mean?

A

how different are the group means compared to the grand mean?

GRAND mean: average score of all observations from all groups

ex: hospital A vs all the hospital means

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21
Q

What does variation within groups mean?

A

not everyone in a group is identical

ex: scores within hospital A

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22
Q

If the groups are very different in an ANOVA test?

A

MS between < MS within

F>1

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23
Q

If the average score of each group is the same (or very similar?

A

MS between ~ MS within

F~1

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24
Q

What is the F distribution?

A

infinite number of f distributions

shape of graph depends on degrees of freedom

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25
Q

What is the critical value of F?

A

the value for which 5% of the area is under the curve and larger than that value

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26
Q

What is the formula for degrees of freedom of NUMERATOR for F?

A

df = #groups - 1

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27
Q

What is the formula for degrees of freedom of the DENOMINATOR for F?

A

univariate ANOVA (1IV, 1DV)

df = N - # groups

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28
Q

What does the numerator of df in F mean?

A

how many groups are being compared

ex: if comparing 4 groups, df between = 3

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29
Q

What does the denominator of df in F mean?

A

total sample size

ex: if you have 250 participants distributed among 4 groups, df within = 246

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30
Q

What does the univariate ANOVA F(3, 246) mean?

A

4 total groups being compared with 250 sample size/observations

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31
Q

When interpreting ANOVA with 3 or more groups, what conclusion can you draw?

A

you can reject the null hypothesis and there is SOME difference between the groups that you cannot exactly determine. You just know that they are not all equal (statistically significant)

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32
Q

How would you find out how the 3 or more groups are different in an ANOVA test?

A

perform post hoc tests

follow up tests/ pairwise comparisons

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33
Q

What are the 3 post hoc tests we need to know?

A
  1. Tukey’s test
  2. Fishers Least Significant Difference (LSD)
    3.Scheffe’s Method
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34
Q

What are descriptive statistics?

A

statistics that help you describe characteristics of your sample.

Primarily measures the central tendency and variability

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35
Q

What are some descriptive statistics we have learned so far?

A

raw scores
arithmetic mean
median
mode
st deviation
number of participants

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36
Q

What are inferential statistics?

A

They describe the likelihood of your results occurring by chance or generalizing beyond your sample

you are inferring things beyond just your sample AKA statistical inference

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37
Q

What are some inferential statistics we have learned so far?

A

students t
point estimate
confidence interval
std error
beta
F (ANOVA)

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38
Q

What is absolute risk?

A

measure of likelihood of a certain event happening

ex: a smoked has 3% overall chance of dying of lung cancer

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39
Q

What is relative risk? (risk ratio)

A

the likelihood of disease among “exposed” compared to the likelihood of disease among “unexposed”

does not provide any info to absolute risk

ex: a smoked is 7x more likely to die of lung cancer than a non-smoker

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40
Q

What is the equation of absolute risk?

A

(participants with disease present in exposed or unexposed) / (total participants in unexposed)

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41
Q

What is the equation of relative risk? (ratio)

A

(absolute risk of disease in exposed) / (absolute risk of disease in unexposed)

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42
Q

What is attributable risk and how is it determined?

A

the amount of risk that can be attributed to the risk factor

absolute risk (exposed) - absolute risk (unexposed/baseline risk)

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43
Q

How do we interpret Risk ratio?

A

RR > 1 = positive association of risk factor and disease

RR < 1 = negative association of risk factor and disease (protective factor)

RR = 1 baseline risk or no association

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44
Q

If RR = 5, what does this mean?

A

5x risk of disease for those exposed to the risk factor vs those that are unexposed

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45
Q

If you have a 2x more likely of getting a disease then the change in risk increased to?

A

100% increase in risk (or 2x the risk)

1 = baseline so if you add 1 more to that you have a 100% increase because you doubled 1

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46
Q

What is the interpretation of RR of 0.80?

A

risk of outcome in the exposed group was reduced by 20% relative to the unexposed group

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47
Q

What is the interpretation of RR of 3.30?

A

risk of outcome in the exposed group was increased by 230% relative to the unexposed group OR the outcome was 3.3 times more likely to occur in the exposed group than in the unexposed group

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48
Q

A study finds that RR = 1.7 and 95% CI: 0.9-2.7. Is there a significant association?

A

NO because 1.0 is within the range of the CI

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49
Q

What is the confidence interval?

A

The range of values, with 95% confidence that is likely to contain the true effect

50
Q

How does the relative risk relate to the CI?

A

if the CI contains a value of 1.0 then the null hypothesis is not rejected = not significant statistical association between risk factor and disease

51
Q

How would you interpret a wide CI?

A

true value lies within a large range of possible values = less precise

52
Q

How would you interpret a narrow CI?

A

true value lies within a small range of possibilities = more precise

53
Q

A study finds RR = 1.7 and CI = 1.02-2.6. Is there a significant association?

A

YES, because 1 lies in the range of the CI

54
Q

What is the definition of risk?

A

chance of outcome of interest out of all possible outcomes

55
Q

What is the definition of odds?

A

the ratio of the change of outcome of interest occurring to the change of the outcome not occuring

56
Q

Where does relative risk come from?

A

Prospective cohort studies = follow forward in time

finding people who will develop the disease

57
Q

Where does the odds ratio come from?

A

case control studies = follow backward in time

already determine who has the disease

58
Q

What is the equation for odds ratio?

A

odds of case (disease) / odds of control (no disease)

59
Q

How do you interpret odds ratio?

A

similar to relative risk (in terms of CI)

60
Q

What is number needed to treat?

A

number of people treated to have impact on one person (how likely is it that a therapy will help an individual person?)

61
Q

What is the number needed to harm?

A

number of people treated to harm one person

62
Q

What is the EER (experimental event rate) formula?

A

probability in treatment group that ended up with an event out of the total #

63
Q

What is the CER (control event rate) formula?

A

how many individuals in your control group ended up with the event out of the total number in the control group

64
Q

What is the absolute risk reduction (ARR)?

A

CER - EER (in absolute value)

65
Q

NNT is in decimal form?

A

1/ARR

66
Q

NNT is in percent form?

A

100/ARR

67
Q

What are some considerations for NNT?

A

in clinical endpoint is devastating (death, heart attack), drugs with high NNT may still be indicated

68
Q

NNT values are time specific so you must

A
  • compare studies with similar time frames
  • must think about timeframe in treatment decisions
69
Q

In an ideal world what would you consider a good NNT?

A

1 because every patient with treatment benefits

70
Q

What is a good range for an NNT?

A

2-5 = effective treatment

71
Q

What is a good NNT for prophylactic treatments (especially those devastating ones)?

A

20-100

72
Q

NNH is calculated for?

A

every side effect/adverse effect

ex: death, blood clot, bleeding

73
Q

Do you want a high NNH or low?

A

high!

74
Q

What is statistical power?

A

the probability that you will find statistical significance with a given sample size, if the alternate hypothesis is true

75
Q

What is statistical power analysis?

A

a statistical analysis conducted BEFORE you begin a study that estimates the necessary sample size to detect a statistically significant relationship (in percentage)

76
Q

As you have larger between group differences, you need a (smaller/larger) number of observations?

A

smaller

77
Q

As you have smaller within group differences, you need (smaller/larger) number of observations?

A

smaller

78
Q

A type 1 error is what?

A

reject the null hypothesis BUT there is NOT statistical significance in the test so you have a false POSITIVE

this is also known as statistical alpha

79
Q

A type II error is?

A

you know that there IS statistical significance in the variables (falling under statistical beta) but you fail to reject the null hypothesis you you have a false NEGATIVE

you should have found something but you didnt

80
Q

Are statistical beta and regression beta the same thing?

A

NO

81
Q

For statistical alpha of 0.5%, what type of error does this fall under?

A

type I

82
Q

What statistical power do we ideally want?

A

80% (higher scores=better outcome)

83
Q

Most studies want to avoid what type of error?

A

type I (statistical alpha)

FP - don’t want to claim something works but it actually doesnt

84
Q

Risk of type I error and type II error are (inversely/directly) proportional

A

inversely

85
Q

What is power analysis?

A

a procedure that estimates an appropriate sample size to find an effect

usually performed with computer programs

86
Q

What is the purpose of Pearson’s correlation?

A

measures how closely related 2 CONTINUOUS variables are (linear relationship between 2 numerical measurements)

87
Q

What are the ranges for Pearson’s Correlation?

A

Range: -1 to +1
(+/-) indicate slope

r=-1 perfect negative correlation
r=1 perfect positive correlation
r=0 no correlation

88
Q

The smallest correlation would be a Pearson’s coefficient of?

A

something closest to 0

89
Q

How do you interpret Pearson’s r? r(698) = -0.09

A

there is a negative linear correlation (-)0.09

698 = degrees of freedom
df = N - 2
N = 700 observations

90
Q

What is considered a small correlation?

A

r=0.10 or -0.10

91
Q

What is considered a medium correlation?

A

r=0.30 or -0.30

92
Q

What is considered a large correlation?

A

r=0.50 or -0.50

93
Q

What is considered a stronger correlation?

A

more clustering around the line of best fit (r closer to -/+1)

94
Q

How would you interpret a straight horizontal or vertical line for Pearsons correlation?

A

r = 0 (non zero slope)

95
Q

What Pearsons coefficient would be a graph with a NONlinear graph?

A

nonzero slope
r=0

96
Q

What is a validation study?

A

comparing a new test(experimental test) to the gold standard

97
Q

For correlation analysis and linear regression analysis where you are comparing 2 variables you report (r/r^2)?

A

r

98
Q

For multiple regression analysis you report?

A

r^2

99
Q

What is the effect size of an r^2?

A

r^2=0.01 small
r^2=0.10 medium
r^2=0.25 large

range = 0 to 1

100
Q

What is the chi squared test?

A

counting things and trying to see if one group has more of something than of something else

IV = categorical
DV = frequency (converted into a percent)

101
Q

Chi squared in common in what type of research?

A

adverse events

102
Q

What is analysis of covariance? (ANCOVA)

A

compares the scores of 2+ groups using statistic F while CONTROLLING a potential confound (COVARIATE)

IV: categorical
DV: continuous
covariate: continuous

103
Q

When can you assume they used ANCOVA data?

A

analysis was adjusted, analysis was estimated, analysis was corrected for

104
Q

What is the difference between clinical and statistical significance?

A

clinical significance - importance of a research result in terms of the symptom relief you can expect for your patient

statistical significance - how likely something occured to chance

105
Q

What are observational studies?

A

hypothesis generating
Ex: case reports/studies, cross section, case control, cohort studies

106
Q

What studies are level I (HIGH)?

A

well designed randomized controlled trials

107
Q

What studies are level II (Good)?

A

well designed controlled un-randomized trials, cohort or case control analytic studies, multiple time series with or without intervention

108
Q

What studies are level III (POOR)?

A

case reports/series
cross sectional studies
reports of expert committee/organizations

109
Q

Random subject selection underpins what?

A

statistical inference which helps ensure external validity

110
Q

Random assignment (prevents/promotes) selection bias, which means that differences in study outcomes are due to study treatments and not from confounding factors

A

prevents

111
Q

Random selection refers to

A

sampling

112
Q

Random assignment refers to

A

group assignment

113
Q

What is sensitivity?

A

accuracy of test to correctly identify all individuals in a population who have a particular disease

true positive/detection rate

sensitive to disease

114
Q

What is specificity?

A

accuracy of the screening procedure to correctly identify those who do no have the disorder

true negative

specific to health

115
Q

What is considered good range to have specificity and sensitivity?

A

70% sensitivity and specificity

116
Q

What are the basic concepts in epidemiology?

A

morbidity
mortality
indidence
prevalence

117
Q

What is incidence?

A

probably that healthy people will develop a disease over a specific period of time

rate at which new disease occurs in a group of people who are disease free

AKA attack rate, risk, probability of developing a disease

come from prospective cohort studies

118
Q

How do you calculate incidence?

A

number of new cases of disease during specific period (1yr)/size of population at risk during specific period

denominator is usually standardized (100,1000,10000)

119
Q

What is prevalence?

A

probability of people having a specific disease at a given time (coming from cross sectional studies)

these people already have the disease from the past at a given time

120
Q

How do you calculate prevalence?

A

number of existing cases during specified point or period/ size of population at risk during specified point or period

expressed as percentage

expressed relative age, gender, race, geographic regions

IPE - Winter OD2 (2 decks)

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