Biostats (Segars) Flashcards

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1
Q

___ is a research perspective which states there will be no true difference between groups being compared
BIG STAR

A

null hypothesis

most conservative and commonly utilized

either accept or reject this perspective, based on statistical analysis

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2
Q

How many standard deviations..?
99.7%: __
68%: __
95%: __

A

3

1

2

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3
Q

positively skewed graph…
which direction is the tail pointing?
relationship of the mean to the median?

A

tail points to the right

mean higher than median (mean>median)

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4
Q

negatively skewed graph…
which direction is the tail pointing?
relationship of mean to the median?

A

tail points to the left

mean lower than median (mean

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5
Q

this data type is dichotomous/binary; non-ranked named categories

has NO magnitude/ NO consistency of scale

A

Nominal

Gender, occupation class, party affiliation, above 5 ft or below 5 ft tall

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6
Q

this data type has ranked categories; non-equal-distance

YES magnitude/ NO consistency of scale

A

Ordinal

> 3 mos, <3 mos, > 6 mos; strongly disagree, somewhat disagree, somewhat agree, strongly agree

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7
Q

this data type has order, magnitude and equal intervals of scale (units)

YES magnitude/ YES consistency of scale

A

Interval

living siblings (number), Age (in yrs), Temp, BP, creatinine, weight

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8
Q

this test for interval type data assesses for equal variances between groups
BIG STAR

A

Levene’s test

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9
Q

1st question to ask to select the correct statistical test…

A

What DATA LEVEL is being recorded?

a) Does the data have MAGNITUDE? (yes/no)
b) Does the data have a fixed, measurable INTERVAL along the entire scale (yes/no)?

this gets you on the right sheet

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10
Q

2nd question to ask to select the correct statistical test…

A

What TYPE OF COMPARISON/ASSESSMENT is desired?

1) correlation
2) Regression (prediction/association)
3) Survival comparison (time)
4) Group comparison (most common)

*frequencies/counts/proportions

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11
Q

this type of comparison /assessment provides a QUANTITATIVE measure of the STRENGTH and DIRECTION of a relationship between variables (range from -1.0 to +1.0)

A

Correlation

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12
Q

Name the CORRELATION test for…
Nominal: ___
Ordinal: ___
Interval: ___

A

nominal=contingency coefficient
ordinal=spearman correlation
interval=pearson correlation

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13
Q

___ correlation just assesses for LINEAR correlation

BIG STAR

A

Pearson

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14
Q

this type of comparison/assessment compares the proportion of events over TIME, or TIME-TO events, between groups (ongoing progression)

A

Survival tests

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15
Q

Survival tests commonly represented by a __ curve

A

Kaplan-meier

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16
Q

Name the SURVIVAL test for…
Nominal: ___
Ordinal: ___
Interval: ___

A

nominal=Log-rank
ordinal=Cox-proportional Hazards
interval=Kaplan-meier

all can be represented by a Kaplan-meier curve

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17
Q

this type of comparison/assessment provides a measure of the relationship between variables by allowing the prediction about the dependent, or outcome, variable (DV) knowning the value/category of independent variables (IV)

A

Regressions

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18
Q

Name the REGRESSION tests for…
Nominal: ___
Ordinal: ___
Interval: ___

A

nominal=logistic regression
ordinal=multinomial logistic regression
interval=linear regression

19
Q

3rd question to ask to select the correct statistical test?

A

HOW MANY GROUPS are being compared?

2 or 3 or more groups

20
Q

Name the tests for Nominal data, 2 groups of independent data

A
  • (pearson’s) Chi-square

- Fisher’s exact –> greater than 2 groups w/EXPECTED cell count of <5

21
Q

For nominal data, >3 groups with statistically significant findings, you must perform what analysis to determine which groups are different?

A

Post-hoc testing –> Bonferroni test of Inequality

22
Q

Nominal test for 2 groups of paired/related data…

A

McNemar test

23
Q

Nominal test for >3 groups of paired/related data

A

Cochran

24
Q

Ordinal test for 2 groups of independent data..

A

Mann-whitney test

25
Q

ordinal test for >3 groups of independent data..

A

Kruskal-Wallis test

26
Q

Post-hoc test for ordinal data, >3 groups

A

Student-Newman-Keul
Dunnett
Dunn

27
Q

Ordinal test for 2 groups of paired/related data…

A

Wilcoxon Signed Rank test

28
Q

ordinal test for >3 groups of paired/related data…

A

Friedman test

29
Q

Interval test for 2 groups of independent data…

A

Student t-test

30
Q

Interval test for >3 groups of independent data…

A

ANOVA (1 DV) or MANOVA (>2 DVs)

31
Q

Interval test for >3 groups of independent data w/confounders…

A

ANCOVA or MANCOVA

32
Q

interval test for 2 groups of paired/related data…

A

paired t-test

33
Q

interval test for >3 groups of paired/related data…

A

Repeated measures ANOVA (1 DV)
OR
Repeated measures MANVOA (>2 DVs)

34
Q

post-hoc tests for interval data…

A
Bonferronie
Tukey
Scheffe
Dunn
Dunnett
Student-Newman-Keul
35
Q

__ is a CORRELATION TEST showing relationship or agreement between evaluators (consistency of “decisions”, “determinations”)

A

Kappa Statistic

36
Q

Kappa interpretation:
__=the observers perfectly “classify” everyone exactly the same way
__=there is no relationship at all between the observers “classifications”, above the agreement that would be expected by chance
__=the observers “classify” everyone exactly the opposite of each other

A

+1

0

-1

37
Q

4th question to ask to select the correct statistical test?

A

Is the data INDEPENDENT or RELATED (PAIRED)?

-Data from the same (paired) or different groups (independent)

38
Q

__ is also known as alpha error and is a REJECTION of the null hypothesis when it is actually TRUE, and you SHOULD HAVE ACCEPTED IT

A

Type 1 error

39
Q

__ is also known as beta error and is NOT REJECTING the null hypothesis when it is actually FALSE, and you SHOULD HAVE REJECTED IT

A

Type 2 error

40
Q

The larger the sample size, the greater the likelihood (ability) of detecting a difference if one truly exists. This has an increase in ___

A

Power –> the ability of a study design to detect a true difference if one truly exists between group-comparisons, and therefore the level of accuracy in correctly accepting/rejecting the Null hypothesis

41
Q

Add in what with Alpha (type 1) and Beta (type 2) error rates and confidence interval?
BIG STAR

A

Add in anticipated drop-outs or loss to follow-ups

42
Q

p-value should be ___ to be statistically significant

A

<0.05 (less than 5%)

43
Q

what does a 95% CI really mean?

A

We are 95% confident that the “true” difference (0) or relationship (1) between the groups is contained within the confidence interval range

44
Q

how do you know if the CI is NOT SIGNIFICANT?

A

if CI crosses 1.0 for ratios (OR/RR/HR)

i.e., 0.78-1.01