NCS Statistical Analysis

Question 1

what are common incorrect assumptions in statistics

Answer 1

you can use popular comparison tests aka t tests
groups are equal at baseline
groups are normally distributed

Question 2

what are the 4 types of data

Answer 2

nominal, ordinal, interval, ratio

Question 3

male or female is an example of what kind of data

Answer 3

nominal data

Question 4

why is nominal data not great for clinical research

Answer 4

it is less sensitive and more difficult to demonstrate significant change

Question 5

pain NRS or MMT grades are examples of what kind of data

Answer 5

ordinal data

Question 6

mile markers or temperature in C or F are examples of what kind of data

Answer 6

interval data

Question 7

weight, temperature in K, 0-100% scoring on a test are examples of what kind of data

Answer 7

ratio data

Question 8

what type of data is the easiest and most sensitive

Answer 8

ratio

Question 9

Bob collects data for his study, this is an example of what kind of data

Answer 9

primary data

Question 10

Bob collects data for his study. A few years later, he then uses that same data for another study. this is an example of what kind of data

Answer 10

secondary data

Question 11

Bob is looking to find out if there is a trend between patient admissions and adequate staffing in the ED over the past 5 years using EMR. This is an example of what kind of data

Answer 11

secondary data

Question 12

what is continuous data

Answer 12

ratio or interval data

Question 13

what is categorical data

Answer 13

ordinal or nominal data

Question 14

what are the parametric assumptions

Answer 14

observations are independent
the data is normally distributed
variance is the same within groups
can only be used for ratio or interval data

Question 15

true or false: it is easy to demonstrate meaningful effect sizes in nonparametric data

Answer 15

false - it is easier in parametric data

Question 16

Tyler falls into the 75th percentile of students in his cohort. this is an example of parametric or nonparametric data

Answer 16

nonparametric (ranks/proportions)

Question 17

according to central limit theorem, a sample distribution becomes more normal or abnormal as the sample size increases?

Answer 17

abnormal

Question 18

according to central limit theorem, at what sample size/n can you not assume normal distribution

Answer 18

n > 30

Question 19

you are looking to determine if there is a significant difference between data sets, what tests can yo u use

Answer 19

kolmogrov-smirnov or shapiro-wilks

Question 20

Bob is conducting a study for a new intervention. His new intervention demonstrates clinical improvement but he does not recruit enough participants to reject his hypothesis that it is better than the standard of care. This is an example of what kind of error

Answer 20

type 1 error

Question 21

Bob is conducting a study for a new intervention. His new intervention is not better than the standard of care but in his analysis he chose the wrong test and it produced a statistically significant finding. This is an example of what kind of error

Answer 21

type 2 error

Question 22

Bob is analyzing nonparametric data using a test of proportions. what test should he use?

Answer 22

Chi squared

Question 23

Bob is analyzing outcomes for an intervention group and control group that was not matched, what should he use if the data is normally distributed

Answer 23

parametric t test

Question 24

Bob is analyzing outcomes for an intervention group and control group that was not matched, what should he use if the data is not normally distributed

Answer 24

nonparametric mann whitney u test

Question 25

Bob is analyzing outcomes for an intervention group and control group that was matched, what should he use if the data is normally distributed

Answer 25

parametric paired T test

Question 26

Bob is analyzing outcomes for an intervention group and control group that was matched, what should he use if the data is not normally distributed

Answer 26

non parametric wlcoxon test

Question 27

Bob is analyzing outcomes for an intervention group, a standard of care group, and placebo control group, what should he use if the data is normally distributed

Answer 27

parametric 1 way ANOVA

Question 28

Bob is analyzing outcomes for an intervention group, a standard of care group, and placebo control group, what should he use if the data is not normally distributed

Answer 28

nonparametric kruskal wallis test

Question 29

Bob is analyzing outcomes for matched intervention group, standard of care group, and placebo control group in which there was a experimental period, a wash out period, and a second experimental period, what should he use if the data is normally distributed

Answer 29

parametric repeated measures ANOVA

Question 30

Bob is analyzing outcomes for matched intervention group, standard of care group, and placebo control group in which there was a experimental period, a wash out period, and a second experimental period, what should he use if the data is not normally distributed

Answer 30

non parametric freidmans test

Question 31

you are looking to find if there is an association between exercise time and age, what type of regression analysis will you do

Answer 31

linear regression

Question 32

you are looking to find if there is an association between age, geographic location, and meeting physical activity guidelines, what type of regression analysis will you do

Answer 32

logistic regression

Question 33

the odds ratio between smoking and hypertension is 3.5. which of the following are true: a. smokers are 3.5x more likely to develop hypertension over non smokers b. smokers are 250% increased odds of developing hypertension over non smokers c. smokers are 2.5x more likely to develop hypertension over non smokers d. a and b e. b and c

Answer 33

d. a and b

Question 34

the odds ratio between exercising and obesity is -0.75. which of the following are true: a. exercisers are 0.75x less likely to develop obesity than non exercisers b. exercisers are 1.33x more likely to not develop obesity than non exercisers c. exercisers are 0.25x less likely to develop obesity than non exercisers d. a and b e. b and c

Answer 34

d. a and b

Question 35

Bob is analyzing data from a control and experimental group to determine associations, assuming the data is normally distributed what type of test should he use

Answer 35

parametric pearson product

Question 36

Bob is analyzing data from a control and experimental group to determine associations, assuming the data is not normally distributed what type of test should he use

Answer 36

nonparametric kendall tau

Question 37

Bob is analyzing data from a waitlist, standard of care, and experimental group to determine associations, assuming the data is normally distributed what type of test should he use

Answer 37

parametric pearson product

Question 38

Bob is analyzing data from a waitlist, standard of care, and experimental group to determine associations, assuming the data is not normally distributed what type of test should he use

Answer 38

non parametric kendall tau

Question 39

Bob is analyzing the outcomes/associations of therapeutic exercise on neck pain vs waitlist control. assuming the data is normally distributed, what test should he use

Answer 39

parametric linear regression

Question 40

Bob is analyzing the outcomes/associations of steriods, modalities, and therapeutic exercise on neck pain. assuming the data is not normally distributed, what test should he use

Answer 40

nonparametric logistic regression

Question 41

Bob is analyzing the outcomes/associations of steriods, modalities, and therapeutic exercise on neck pain and NDI score. assuming the data is not normally distributed, what test should he use

Answer 41

discriminate analysis

Question 42

Bob is researching different interventions for his patient. What statistic should Bob look at to determine if a particular intervention will be clinically meaningful to his patient? a. p value of <0.05 b. p value of <0.001 c. effect size

Answer 42

c. effect size

Question 43

Bob is researching different interventions for his patient. In reading an article about a particular intervention, Bob sees that the confidence interval crosses zero. how should bob interpret this

Answer 43

there is no difference between groups so the intervention may not be effective

Question 44

Bob is researching different interventions for his patient. In reading an article about a particular intervention, Bob sees that the confidence interval is very wide. how should bob interpret this a. this intervention is helpful and precise b. this intervention is helpful but not precise c. this intervention will not differ from the control

Answer 44

b. this intervention is helpful but not precise

Question 45

Bob is researching different interventions for his patient. In reading an article about a particular intervention, Bob sees that the confidence interval is very narrow. how should bob interpret this a. this intervention is helpful and precise b. this intervention is helpful but not precise c. this intervention will not differ from the control

Answer 45

a. this intervention is helpful and precise

Question 46

the AIMS is an example of an outcome measures that uses what kind of data a. nominal b. ordinal c. interval d. ratio

Answer 46

a. nominal

Question 47

the FIM is an example of an outcome measures that uses what kind of data a. nominal b. ordinal c. interval d. ratio

Answer 47

b. ordinal

Question 48

the Stroke impact scale is an example of an outcome measures that uses what kind of data a. nominal b. ordinal c. interval d. ratio

Answer 48

c. interval

Question 49

distance on the 6MWT is an example of an outcome measures that uses what kind of data a. nominal b. ordinal c. interval d. ratio

Answer 49

d. ratio