Brainscape's Knowledge GenomeTM

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


See full index

Epidemiology > Epi Exam 3 > Flashcards

Epi Exam 3 Flashcards

1
Q

null hypothesis (Ho)

A
  • research perspective which states there will be no (true) difference between the groups being compared
  • most conservative and commonly utilized
  • various statistical-perspectives can be taken: superiority; non-inferiority; equivalency
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

3 key attributes of data measurments

A
  • order/magnitude
  • consistency of scale/equal distances
  • rational absolute zero
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

nominal (dichotomous/binary; non-ranked; Named categories)

A
  • NO order or magnitude
  • NO consistency of scale or equal distances

are simply labeled-variables without quantitative characteristics

anything that has 2 categories

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

ordinal (ordered; rank-able categoreis: non-equal-distance)

A
  • YES order or magnitude

- NO consistency of scale or equal distances

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

interval/ratio (order and magnitude and equal distances)

A

Interval: arbitrary zero value (zero doesn’t mean absence)
Ratio: absolute (rational) zero value (zero means absence of measurement value; e.g. physiological parameters)

  • YES order or magnitude
  • YES consistency of scale or equal distances

e.g. age in years, body weight, height, temperature
usually see units associated with this type of data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

discrete data

A

categorized data

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

continuous data

A

continuous evenness of spacing

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

changing levels of measurement of data

A

can go down in specificity/detail of data measurement (levels) but never up

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

descriptive statistics

A

non-comparative, simple description of various elements of the study’s data

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

measures of central tendency (dispersion or spread)

A
  • mean/median/mode
  • minimum/maximum/range
  • interquartile range (IQR)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

variance

A

average of the squared-differences in each individual measurement value (x) and the groups’ mean (xbar)

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

standard deviation

A

square root of variance value (restores units of mean)

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

normally distributed graphical representation of data

A
  • symmetrical

- mean and median are near equal

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

normal curve: area under the curve

  • 1 SD
  • 2 SD
  • 3 SD
A
  • 1 SD: 68%
  • 2 SD: 95%
  • 3 SD: 99.7%
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

positive skewed

A
  • distribution is skewed anytime the mean differs from the median
  • when mean is higher than median
  • tail pointing to the right
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

negative skewed

A
  • when mean is lower than median

- tail pointing to the left

17
Q

kurtosis

A
  • a measure of the extent to which observation cluster around the mean
  • for a normal distribution, the value of the kurtosis statistic is 0
18
Q

positive kurtosis

A

more clustered

19
Q

negative kurtosis

A

less clustered

20
Q

do not calculate ____ for discrete data

A

mean

21
Q

4 questions to select the correct statistical test

A
  1. what data level is being recorded: magnitude and consistency of scale
  2. what type of comparison/assessment is desired: correlation; regression; survival comparison (time); group comparison
  3. how many groups are being compared: 2 or 3+ study groups
  4. is the data independent or related/paired [data from the same (paired) or different (independent) study groups]
22
Q

correlation (r)

A
  • buzz words: correlation; association/relationship

- provides a quantitative measure of the strength and direction of a relationship between variables (-1 –> +1)

23
Q

partial correlation

A

(only for interval data/pearson correlation; with assumptions)

-a correlation that controls for confounding variables

24
Q

correlation test for:

  • nominal
  • ordinal
  • interval
A
  • nominal: contingency coefficient
  • ordinal: spearman correlation
  • interval: pearson correlation (p>0.05 just means there is no linear correlation, may still be a non-linear correlation)
25
Q

kappa statistic

A

correlation test showing relationship of agreement between/consistency of ‘decisions’ ‘determinations’

+1: the observers perfectly ‘classify’ everyone exactly the same way

0: no relationship at all between the observers ‘classifications’ above the agreement that would be expected by chance
- 1: observers ‘classify’ everyone exactly the opposite of each other

26
Q

regression

A
  • outcome prediction/association
  • provide a measure of the relationship between variables by allowing the prediction about the dependent, or outcome, variable (DV) knowing the value/category of independent variables (IVs)
  • also able to calculate odds ratio (OR) for a measure of association and control for confounders
27
Q

regression test for:

  • nominal
  • ordinal
  • interval
A
  • nominal: logistic regression
  • ordinal: multinomial logistic regression
  • interval: linear regression
28
Q

survival tests

A
  • compares the proportion of events over time; event-occurrence; or time-to events, between groups (ongoing progression)
  • commonly represented by a Kaplan-Meier curve
  • e.g. number of days until event occurs
29
Q

survival test for:

A
  • nominal: Log-rank test
  • ordinal: cox-proportional hazards test
  • interval: kaplan-meier test
30
Q

independent nominal data:

  • 2 groups of independent data
  • 3 or more groups of independent data
  • 2 or more groups with expected cell count less than 5
A
  • 2 groups of independent data: (Pearson’s) Chi-square test
  • 3 or more groups of independent data: Chi-square test of independence
  • 2 or more groups with expected cell count less than 5: Fisher’s Exact test
31
Q

post-hoc testing for independent nominal data with 3 or more groups of independent data

A
  • bonferroni test of inequality (bonferroni correction)

- bonferroni adjusts the p value for number of comparisons being made

32
Q

paired/related nominal data:

  • 2 groups of paired/related data
  • 3 groups of paired/related data
A
  • 2 groups of paired/related data: McNemar test

- 3 groups of paired/related data: Cochran followed by bonferroni to determine where significant difference was found

33
Q

independent ordinal data:

  • 2 groups of independent data
  • 3 or more groups of independent data
A
  • 2 groups of independent data: Mann-Whitney test
  • 3 or more groups of independent data: Kruskal-Wallis test
  • both compares the median values between groups
  • if 3+ group comparison significant –> post-hoc test
34
Q

paired/related ordinal data:

  • 2 groups of paired/related data
  • 3 or more groups of paired/related data
A
  • 2 groups of paired/related data: wilcoxon signed rank test
  • 3 or more groups of paired/related data: friedman test
  • both tests compares the median values between groups
  • if 3+ group comparison significant –> post-hoc test
35
Q

ordinal data:

post-hoc tests for 3 or more group comparisons

A
  • student-newman-keul test: all groups must be equal in size
  • dunnett test: every group compared to one single control (center of wheel example)
  • dunn test: useful when all groups are not the same size
36
Q

independent interval data:

  • 2 groups of independent data
  • 3 or more groups of independent data
A
  • 2 groups of independent data: student t-test
  • 3 or more groups of independent data: analysis of variance AN(C)OVA
  • both tests compares the means of all groups (ANOVA against a single DV)
  • if 3+ group comparison significant, must perform a post-hoc test
37
Q

paired/related interval data:

  • 2 groups of paired/related data
  • 3 or more groups of paired/related data
A
  • 2 groups of paired/related data: paired t-test (compares the mean values between groups that are related)
  • 3 or more groups of paired/related data: repeated measures AN(C)OVA (compares the means of all groups (along with intra- and inter-group variations) of related data against a single DV)

-if 3+ group comparison significant, must perform a post-hoc test to determine where differences is (are)

38
Q

interval data:

post-hoc tests for 3 or more group comparisons

A
  • student-newman-keul test: all groups must be equal in size
  • dunnett test: every group compared to one single control (center of wheel example)
  • dunn test: useful when all groups are not the same size
  • tukey (slightly more conservative than the Stu.N.K.) or scheffe (less affected by violations in normality and homogeneity of variances-most conservative) tests: compares all pairwise comparison possible; all groups must be equal in size
  • bonferroni correction: adjust the p value for number of comparisons being made

Epidemiology (9 decks)

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