Final: Lecutres 22-24

Question 0

Nominal (Dichotomous/Binary)

Answer 0

• No order or Rank, Non-Ranked Categories
• No magnitude/ no consistency of scale/ no rational zero
• Dichotomous breaks all the rules! Call it nominal b/c it’s only two. (Ex. high blood pressure vs. normal)
• Gender and Handed-ness ex.

Question 1

3 Key Attributes of Data (variables)

Answer 1

1. Magnitude (or Dimensionality) bigger is more, lower is less
2. Consistency of scale (or Fixed Interval) equal, measurable spacing between units.
3. Rational Zero (ex. blood pressure can not be negative)

•Each attribute can be assessed with a “Yes” or “No” response

Question 2

Ordinal (Ranked Categories!!)

Answer 2

• Non-Equal-Distance
• Yes magnitude/ No consistency of scale/ No rational zero
• Levels of Intimidations, pain scale ex.

Question 3

Interval/Ratio (Order/Magnitude & Equal intervals-of-scale)

Answer 3

• Yes magnitude/ Yes consistency of scale/ No (Interval) or Yes (Ratio) Rational zero
• All numerical scales with TRUE units
• Number of living siblings and Age Ex.

Question 4

T/F After data is collected, you can always go up in specificity/detail of data measurement (levels).

Answer 4

•FALSE, you can go down, but never up!

Question 5

Is a mental health scale, where they rank certain questions with strongly agree/disagree ect. interval or ordinal?

Answer 5

• Just for each individual question, it’s Ordinal.

* But if you rank each question and add up the scores, it’s Interval

Question 6

What data level is each survey item? (A-Nominal, B-Ordinal, C-Interval)

1. Age
2. Sex
3. Current Occupation
4. Months Homeless
5. Regarding your overall stress level the last 3 months, how often have you felt: out of control? sick? ect.
6. How would you describe your overall health? very good, good, ect
7. How many times in the last year have you seen doctor/dentist?

Answer 6

1. C
2. A
3. A
4. C
5. B
6. B
7. C

Question 7

Measures of Central Tendency and Dispersion

Answer 7

• Mean/Median/Mode
• Outliers
• Minimum/Maximum/Range
• Interquartile Range (IQR)

Question 8

Variance

Answer 8

•Difference in each individual measurement value and the groups’ mean

Question 9

Standard Deviation (SD)

Answer 9

•Square root of variance value (restores units of mean)

Question 10

Parametric tests

Answer 10

• Stats test useful for Normally-Distributed data

* Symmetrical plot

Question 11

Positively Skewed Plot

Answer 11

• Asymmetrical distribution with one “tail” longer than another
• Skewed anytime the median differs from the mean!
• When mean higher than median, skewed right (positive)

Question 12

In a Negatively Skewed graph, the mean is _______ than the median.

Answer 12

•Lower

Question 13

Required Assumptions of Interval Data

Answer 13

1. Normally-distributed around a known mean
2. Equal variances (SD) Levene’s test** assess for equal variance between groups
3. Randomly-derived and independent

Question 14

Handling Interval data that is not normally-distributed

Answer 14

• ALWAYS run descriptive statistics and graphs
• Use a statistical test that does not require the data to be normally-distributed (non-parametric tests)
• Transform the data to a standardized “score” (z-score); hoping that this transformation will cause the data to become normally-distributed in order to use a parametric test

Question 15

Type __ errors rejects the Null hypothesis when you shouldn’t, and Type __ is when you should reject it, but the data says not to.

Answer 15

• 1, (false positive)

* 2 (false negative)

Question 16

Statistical tests compare differences in variables or to evaluate relationships between them:

Answer 16

1. A test statistic value is calculated, then,
2. Compared to the appropriate table of probabilities for that test, then
3. A probability (p)** value is obtained, based on the probability of observing, due to chance alone, a test is statistic value as extreme or more extreme than actually observes (probability of making type 1 error)

Question 17

If p value is lower than pre-selecting a priori value (usually .05) then we say it’s?

Answer 17

• Statistically Significant

* If less than .05, we REJECT the Null Hypothesis (just says there is a difference, not by how much)

Question 18

Interpretation of p value***

Answer 18

•Be able to say what p value represents on test (EXACT WORDS) 5 different ways:

• The probability of making a Type 1 error if the Null Hypothesis is rejected.
• The probability of erroneously claiming a difference between groups when one does not really exist

Question 19

Impacts to Statistical Significance

Answer 19

• Power: the ability of a study design and its methodology to detect a true difference if one truly exists (The level of accuracy in correctly accepting/rejecting the Null Hypothesis)
• Sample size: the larger the sample size, the greater the likelihood of detecting a difference if one truly exists. (Increase in Power)

Question 20

Sample Size Determination

Answer 20

• Difference between groups deemed significant: the smaller the difference between groups necessary to be considered “significant” the greater the number needed
• Baseline rate of outcome (known/estimated)
• Alpha and Beta Error rates (power) **Add in anticipated drop-outs or loss to follow-ups

Question 21

Statistical significane

Answer 21

• Comparisons of groups generates only a statistical estimate of the “true” yet unknown difference between groups (a Point estimate)
• Spread (V/SD) in estimates of group comparisions can aid in interpretation
• Confidence Interval (CI) level of confidence you believe reality (the real difference) is located

Question 22

*If CI crosses __ (for OR/RR/HR) or __ (interval variables) = NOT SIGNFIICANT

Answer 22

• 1.0

* 0.0

Question 23

4 Key Questions to Selecting the Correct Statistical Test

Answer 23

1. What TYPE OF DATA is being collected/evaluated? (does it have MAGNITUDE? does the the data have a fixed, measurable INTERVAL?)
2. What TYPE OF COMPARISON/ASSESSMENT is desired? (correlation test)
3. HOW MANY GROUPS are being compared? (2 or 3 or more)
4. Is the data INDEPENDENT or RELATED (PAIRED)? (data from the same (paired) or different groups (independent) (related data come from same human, before/after, pre/post ect)

Question 24

Correlation provides quantitative measure of the _______ and _______ of a relationship between variables.

Answer 24

• Strength

* Direction

Question 25

Nominal Correlation test =

Ordinal Correlation test =

Interval Correlation test =

Answer 25

• Contingency Coefficient
• Spearman Correlation
• Pearson Correlation (p>0.05 just means there is no Linear correlation, there still may be a Non-linear correlation present)

Question 26

Time-to-Event/Event-Occurrence—> survival test

Answer 26

• Nominal Survival test= Log-Rank Test
• Ordinal: Cox-Proportional Hazards test
• Interval: Kaplan-Meier test
• All can be represented on Kaplan-Meier curve

Question 27

Regressions

Answer 27

• Provide a measure of relationship between variables by allowing the prediction about the dependent, or outcome, variable (DV) knowing the value/rank of others independent variable (IV)
• Also able to calculate OR for a Measure of Ass.

Question 28

Know sheets to look at the rest of the tests

Answer 28

•Look at last slide of class 22-24 to practice!