Advanced Statistics

Question 1

Survival analysis is used when:

Answer 1

1. considering long-term effects
2. understanding prognosis and trx effectiveness.

Question 2

All questions regarding survival analysis will have a ______ component.

Answer 2

Time

Question 3

What type of distribution does survival time data typically have?

Answer 3

positive skewness

Question 4

What are the components of censored observation?

Answer 4

• Includes those who have not reached the terminal event by end of the study
• leads to data that is incomplete
• leads to underestimation of event occurrences.

Question 5

What are the important characteristics of the Kaplan-Meier curve?

Answer 5

1. Analyzes the probability of an event at specific time intervals
2. Generates a step function that will change survival estimate each time a pt reaches a terminal event
3. accounts for the censored observations
4. Often reported with confidence intervals to better apply population parameters

Question 6

What is the median survival time?

Answer 6

the point at which cumulative survival function = .5 (50th percentile)

Question 7

the mean survival time is estimated as:

Answer 7

an area under the K - M curve

Question 8

What is a hazard rate? how is it estimated?

Answer 8

the rate at which how rapidly a subject will experience a terminal event
estimated by the slope of the line fitted to K - M curve

Question 9

What is a hazard ratio?

Answer 9

compares how often a particular terminal event happens between 2 groups.

Question 10

Hazard ratio will tell us if a group is:

Answer 10

faster, slower, or event rates are the same in both groups.

Question 11

When is a log-rank test at its best?

Answer 11

When there are equal proportions

Question 12

What are the limitations of the Log Rank Test?

Answer 12

1. can only test one variable at a time
2. cannot control for confounders or other risk factors
3. cannot include interaction terms

Question 13

What would be a null and alternative hypothesis for survival analyses?

Answer 13

null: the groups have identical distribution curves
alternative: the groups have different distribution curves

Question 14

The COX proportional hazard model is better than the LOG rank if you want to what?

Answer 14

control for confounding variables

Question 15

What is the goal of the factor analysis?

Answer 15

1. Seeks to understand whether and to what extent items from a survey or scale reflect specific contracts
2. Provides information about reliability, item quality, and construct validity
3. High sensitivity to identify problematic items and assess the number of factors

Question 16

What are the 2 types of factor analysis?

Answer 16

exploratory factor analysis
confirmatory factor analysis

Question 17

factor analysis allows us to ___________ complex variables.

Answer 17

simplify

Question 18

factor analysis will function to find _____________ between variables.

Answer 18

similarities

Question 19

What are the 4 uses and goals of exploratory factor analysis?

Answer 19

1. explore the possible underlying factor structure of a set of observed variables
2. identify the underlying factor structure
3. describe and identify the number of factors
4. provide a means of explaining variation amongst variables.

Question 20

What assumptions must we make to run an exploratory factorial analysis?

Answer 20

1. continuous data
2. normal distribution
3. sample size is large enough (greater than 200 with more than 3 observations per variable).
4. correlation is greater than .2 between variables.

Question 21

What are the limitations of exploratory factor analysis?

Answer 21

1. subjective analysis
2. variables may not always be generalizable to the population
3. no causal inferences can be made

Question 22

A confirmatory factor analysis will test the hypothesis that a relationship exists between:

Answer 22

the observed variables and an identified factor.

Question 23

What are limitatios to a confirmatory factorial analysis?

Answer 23

sample size must be large
very sensitive to outliers and missing data.

Question 24

What is a cluster analysis?

Answer 24

an exploratory data analysis tool for organizing observed data into meaningful clusters based on combinations of variables.

Question 25

What is agglomerative hierarchical clustering?

Answer 25

bottom-up –> 1 piece of data set and merges it with others to form larger groups.

Question 26

What is divisive hierarchial clustering?

Answer 26

top down –> starts w/ whole data set and partitions data step by step.

Question 27

what are limitations to hierarchial clustering?

Answer 27

arbitrary decisions (subjective)
consideration of data types
misinterpretation possible

Question 28

What is non - hierarchical clustering?

Answer 28

data points are grouped into non - overlapping subsets (clusters) such that each object is in exactly one cluster.

Question 29

What is the most widely used clustering?

Answer 29

K - mean clustering

Question 30

What are limitations to K mean clustering?

Answer 30

subjective test

Question 31

how does k - mean clustering occur?

Answer 31

data is classified into K # clusters, and each data point is mapped into the clusters with its nearest mean.

Question 32

What type of cluster analysis woudl you use if you have categorical and continuous data?

Answer 32

2 step clustering or hybrid approach

Question 33

What are some benefits to 2 step clustering?

Answer 33

1. allows for the ability to create clusters on both categorical and continuous variables.
2. number of clusters is automatically determined
3. makes the analysis of a large data set very efficient

Question 34

The cluster quality validation index measures:

Answer 34

how well the general goal of clustering is achieved.

Question 34

The cluster quality validation index measures:

Answer 34

how well the general goal of clustering is achieved.