Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

M2M > Statistics > Flashcards

Statistics Flashcards

1
Q

meta-analysis def

A

single analysis of all existing analyses

never interpreted as primary research

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

steps of meta-analysis

A 
specify question
search for evidence
judge evidence quality
display findings
combine results when possible
conclude with summary of evidence
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

evidence searching

A

PubMed, NIH, etc.
search unpublished findings
search “gray” data/publishings

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

funnel plot axes

A

Odds Ratio scattered against standard error

shows publication bias

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

reasons for association between factor and dz

A 
bias in the sampling of subjects
bias in the measurement of the factor
confounding by another factor
chance
transposition of cause and effect
actually causal
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

qualitative variables

A

“nominal” (eg, gender, hair color, city)

amenable to categorical anaysis only

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

quantitative variables

A

continuous variability with normal distribution
categorical (ordinal)
- dichotomous if only two categories
- ordinal

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

dichotomous data

A

only two categories possible
can exit without hierarchy
- male/female
can exist with hierarchy

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

ordinal data

A

nominal data with more than two possible states and an existing hierarchy, i.e. grades A, B, C, D, F

education level
cancer stage I,II,III,IV
1-year age categories

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

continuous data

A

any value between two other values possible

weight, blood pressure, IQ, etc.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Likert scales

A

Least favorite Most favorite
1 2 3 4 5 6

tracks like continuous data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

measures of central tendency

A

mode - most commonly observer value
median - middle observation in a data set arranged from lowest to highest
mean - the arithmetic average (sum of observations/the number of observations)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

measures of spread

A

range - highest value minus lowest value

variance - a standardized measure of the sum of the differences between each value and the mean value

standard deviation - the square root of the variance, which has special properties when describing a Normal Distribution curve

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

variance definition

A

sum (x-mean)^2 / (n-1)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

standard deviation definition

A

square root of variance

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

frequency distribution

A

conceptually identical to a pile of anything
the center of the pile is the central tendency
the total width of the pile is the range
the amount of scatter is the variance

normal distribution is common in nature
mean = median
the % of subjects with various values can be estimated by the standard deviation

17
Q

normal distribution characteristics

A

mean = median

approximately 67% of values lie within +/- one standard deviation distance from the mean

approximately 95% of values lie within +/- two standard deviation diwstances from the mean

approximately 99% of values lie within +/- three standard deviations of the mean

18
Q

meaning of two standard deviations

A

95% values inside, only 5% outside

19
Q

methods to control for confounding

A

matching

stratification in analysis

adjustment in analysis

  • Direct adjustment (eg, age-adjusted rates)
  • Multivariate analysis
20
Q

Age adjustment

A

Direct method

  • Uses the population distribution of a reference population
  • recompute crude rates against standard to get adjusted rates

Indirect method
- compare observed number of cases to an expected number of cases in a population after generating expected number using the age-specific disease rates of a reference population

21
Q

multivariate adjustment

A

multiple linear regression (beta for slope)
When outcome variable is continuous

multiple logistic regression (Odds Ratio for RR)
When outcome variable is dichotomous

Proportional hazards analysis (Hazard Ratio for RR)
When outcome variable is dichotomous and person-time is an independent variable

22
Q

Inferential Statistics

A

used to describe findings in a study

also used to make yes/no decision on likelihood of chance occurrence

23
Q

Null hypothesis

A

assume no effect

take measurements

disprove (reject) the null hypothesis

24
Q

Alternative hypothesis

A

there is an effect

25
Q

Type I error

A

finding a difference when there isn’t one

26
Q

Type II error

A

finding no difference when there is one

27
Q

real difference and tested difference

A

correctly reject null hypothesis

28
Q

no real difference and no tested difference

A

correctly accept null hypothesis

29
Q

Alpha level

A

tolerance for making a type I error

set at 0.05, means willing to accept a 5% chance of being wrong (reject H0 when you shouldn’t)

Investigator sets the alpha level a-priori

30
Q

p-value

A

estimated probability that the results occurred by chance alone

= risk of making a type I error

if the p-value is equal to or less than the alpha level, the research rejects the null hypothesis and concludes the results are “statistically significant” (yes/no decision)

31
Q

Beta level

A

tolerance for making a type II error

set at 0.20 means willing to accept a 20% chance of being wrong (accept H0 when you shouldn’t)

Investigator sets the beta level a-priori

significant in small sample size studies

32
Q

beta power

A

Power = 1 - beta

33
Q

Confidence intervals

A

The confidence interval gives the range of values within which the true, population effect size can be expected to fall

A 95% confidence interval corresponds to an alpha level of 0.05; there is less than a 5% chance that the true, population effect size is larger or smaller than the bounds of this interval

Note that a small confidence interval provides more confidence that the true population effect size is close to what you found in your study

34
Q

confidence intervals and statistical significance

A

if the confidence interval for a mean or percent difference includes 0, the difference is not statistically significant

If the confidence interval for a relative risk includes one, the difference in risk is not statistically significant

35
Q

statistical vs clinical significance

A

clinical significance relates to the degree of importance of a finding in providing care for patients

A study with a large sample size might find a statistically significant difference that doesn’t matter clinically

A study with a small sample size might have a result that is not statistically significant, but if it were, it would have huge clinical significance

36
Q

t-test

A

use difference in means, standard deviation, and sample size to establish variance?

37
Q

chi-squared statistic

A

comes from categorical (not continuous) data

  • alive/not alive
  • respond/didn’t respond
  • diseased/not diseased
38
Q

OR

A

Odds Ration

39
Q

What affects the chi-squared statistics

A

???

M2M (11 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions