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Naplex Study Tools > Biostatistics > Flashcards

Biostatistics Flashcards

1
Q

Continuous Data

A

equal distance between values, with or without a true meaningful zero (nominal data or interval data respectively)
ratio data- age, height, weight, BP, time
interval data- Celsius and Fahrenheit

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2
Q

Discrete (Categorical) Data

A

nominal data- yes or no; male or female

ordinal data - pain score, NYHA Class I-IV

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3
Q

Mean

A

average

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4
Q

Median

A

Middle number

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5
Q

Mode

A

value that occurs most often

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6
Q

Null hypothesis

A

There is no difference observed

example: metoprolol equals carvedilol

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7
Q

Metoprolol DOES NOT EQUAL Carvedilol (p-value: < 0.05)

A

Reject the Null Hypothesis or Accept the Alternative Hypothesis

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8
Q

Metoprolol DOES EQUAL Carvedilol (p-value: > or equal to 0.05)

A

Accept the Null Hypothesis or Fail to accept the Alternative Hypothesis

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9
Q

Confidence Interval

A

1 - alpha
alpha determines p-value
example: alpha = 0.05
1-alpha= 95% confident that the conclusion is correct

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10
Q

Confidence interval for MEAN data. Significant vs. Non-significant

A

Significant- NO ZERO

Non-significant- Includes ZERO

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11
Q

Confidence interval for RR, OR and HR. Significant vs. Non-significant

A

Significant- DOES NOT include ONE

Non-significant- Includes ONE

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12
Q

Type I error (false positive)

A

Null H0 is rejected in error

alpha= risk of type one error

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13
Q

Type II error

A

Null H0 is accepted in error
Power= 1- beta (probability of avoiding a type II error)
example: Power 80% means the probability of avoiding a type II error equals 20%

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14
Q

Risk

A

= # of subjects with the unfavorable event / # of subjects in that arm of the study

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15
Q

RR (relative risk)-specific to tx group

A

Risk Tx group/ Risk Control group
equal to 1= no difference
> 1: higher risk in tx group
< 1: lower risk in tx group

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16
Q

RR > 1

A

less likely

17
Q

RRR

A

RRR is how much the risk is reduced (less likely)

formula: 1-RR (express as decimal)

18
Q

RR + RRR must equal?

A

ONE

19
Q

ARR (absolute risk reduction)

A

absolute difference between groups
formula- risk (control group)- risk (tx group)
example: 0.12 or 12% means for every 100 patients treated with metoprolol, 12 fewer patients will have HF progression

20
Q

NNT/NNH

A

number of people who need to be treated for a certain period of time in order for 1 patient to benefit

formula: 1/ARR (decimal form)

NNT: 8.3- round up to 9
NNH: 41.9- round down to 41

21
Q

Odds Ratio

A

AD/BC

22
Q

When to use an unpaired student t-test?

A

CONTINUOUS data that is normally distributed with 2 GROUPS

23
Q

When to use an ANOVA test?

A

CONTINUOUS data that is normally distributed with 3 GROUPS

24
Q

When to use Chi-square test?

A

Discrete (categorical) data w/ one to two groups.

OR Fisher’s exact test

25
Q

Sensitivity

A

true positive

- test will be positive in all patients that have the condition

26
Q

Specificity

A

true negative

-test will be negative in all patients that have condition

27
Q

Sensitivity/Specificity of 87%?

A

Sensitivity: 87% of patients with the condition are diagnosed while 13% are not.

Specificity: 87% without the condition are diagnosed correctly while 13% of patients w/o the condition are diagnosed w/ the condition or test positive

28
Q

Case-control study

A

compares patients with DISEASE to those WITHOUT DISEASE (retrospectively)

29
Q

Cohort Study

A

compares EXPOSED patients to NON-EXPOSED (retrospective or prospective)
example: patients taking statins vs patients not taking statins

30
Q

Top 4 medical studies

A
  • Systematic Review/ Meta-analyses
  • RCT
  • Cohort Studies
  • Case-controlled
31
Q

Cost-effectiveness analysis (CEA)

A

most common
- costs are monetary but outcomes are clinical
(MUST BE ONE OUTCOME)

32
Q

cost- utility analysis

A

outcomes based on QALY

33
Q

Cost-minimization analysis

A

cost of interventions that are EQUIVALENT

34
Q

cost-benefit analysis

A

compares benefits and costs in monetary unites ($$$ values)

35
Q

Having a p-value of that is less than alpha (p<0.05) mans what?

A

The probability that a conclusion is incorrect is LESS THAN 5% (1 in 20)

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