Research Misc.

Question 1

Describe Face validity

Answer 1

The extent that a tool measures what it is supposed to from a superficial perspective
(looking at yourself in the face, superficial without a deep dive)

Question 2

Describe concurrent Validity

Answer 2

Comparing a tool to the gold standard (comparing to another current tool)

Question 3

Describe construct validity

Answer 3

How much does a tool measure an abstract concept
(construct=abstract ideas, does it match with the theory)

Question 4

Content validity is what

Answer 4

How much does the tool measure the specific subject matter
(e.g does algebra test have algebra or geometry questions, getting deeper into the content)

Question 5

Validity vs Reliability

Answer 5

Validity: How close to truth. This is why I say people ae not valid. They are far from truth

Reliability: How consistent are you. I say kyrie isn’t reliable b/c them 9 point games

Question 6

What is a quasi-experimental design

Answer 6

Research that seeks to establish causality without manipulation (no randomization)

compared to an experimental design when the independent variable is manipulated (difficult in PT because can’t hide intervention)

Question 7

What is the null hypothesis

Answer 7

Means No relationship between groups.

We want to DISPROVE THIS, meaning prove that there is relationship

Question 8

Independent vs dependent

Answer 8

Input vs output/result

Question 9

What is an alternate hypothesis

Answer 9

When there is a relationship between groups (typically what we want to be correct)

Question 10

Normal curve

Answer 10

Would have mean, median and mode at same point

Question 11

Intra-rater vs inter-rater

Answer 11

Intra-rater in how likely is same person going to get consistent same results

vs

inter-rater is “between” diff researchers how consistent

Question 12

Internal vs external validity

Answer 12

Internal validity - any other reasons for outcomes (confounding factors)

External validity - Is it generalizable

Question 13

Nominal scale

Answer 13

Named, no significance besides the given name

Question 14

Ordinal scale

Answer 14

E.g is Borg RPE scale. Subjective scale with order.

MMT grading. Cant tell exact difference just know order/direction

Question 15

Interval scale

Answer 15

Distance between each is meaningful. E.g is temperature or PH

Question 16

Ratio scale

Answer 16

An absolute zero.
E.g is weight no such thing as negative.

Question 17

T-test

Answer 17

The degree to which TWO groups of data are different. (Means divided by variability of groups)

=Comparing the means of 2 groups to see how diff they are

*z test would be the same only unknown

Question 18

If P<0.05

Answer 18

Reject Null Hypothesis
This means there is a relationship which is what we are looking for

Question 19

If P>0.05

Answer 19

Accept Null hypothesis, there is no relation or change that comes due to independent variable

Question 20

Chi-squared test (X^2 test)

Answer 20

Assesses difference between observed and expected values to determine how they are or are not related.

Question 21

Pearson Correlation Coefficient

Answer 21

Positive correlation: x and y increases. Notice line goes up from left to R

Negative correlation: y increases as x increases
Notice line goes down from R to L

No correlation: random points = 0.0

-1 to 1

closer to -1 or 1 means stronger and more linear in either direction

Question 22

Regression analysis

Answer 22

using correlation coefficients to predict values

Question 23

What percent of people fall within 2 SD

Answer 23

95

Question 23

Standard deviation

Answer 23

Determining how far off value is from mean

T-score for bone uses this

-1 to 1 is healthy

-1 to -2.5 is osteopenia

less than -2.5 is osteoporosis

Use 50 percent to assist you on SD math questions

Question 23

what percent of people fall within 1 SD in normal curve

Answer 23

68

Question 24

What percent of people fall within 3 SD

Answer 24

99.7 (more spread out)

Question 25

ANOVA Testing

Answer 25

Analyzing 3 more data sets

Question 26

Sensitivity

Answer 26

% if pt Correctly identified positives

What percent of true positives were detected

SnOUT
High SENsitive test NEGative result can be confidently ruled OUT

Question 27

Specificity

Answer 27

% of pt Correctly identified negatives

What percent of true negatives were detected

SpIN

High SPecificity and POSitive result means can be confident that positive rules IN

Question 28

Likelihood ratio

Answer 28

Determines how much a diagnostic test increases or decreases likelihood of having condition

Question 29

+LR

Answer 29

Indicates a positive test rules in (higher the number the greater the likelihood that it rules in) starting at 1

Question 30

• LR

Answer 30

Indicates a negative test rules out (lower the number the greater the likelihood that it rules out) starting at 1and decreased towards 0. the smaller the greater likelihood

Question 31

Z-score

Answer 31

Strictly used SD to describe how far from mean (compared to population NOT norms )

Question 32

T score

Answer 32

Compares individual to normative value NOT population (e.g healthy individual) with SD

of sample pop

e.g for bone density T score

Question 33

Alpha level

Answer 33

Determined by researchers…what is the set level for probability of rejecting null hypothesis when it is actually true. Usually set at <0.05

Question 34

P level

Answer 34

The probability of that results are lucky/due to chance if hypothesis is true. meaning typically less than 5% chance that it null hypothesis is true due to luck

If p value is less than alpha level, you rject the null hypothesis

Question 35

List levels of research from most reliable/least bias to least reliable/most bias

Answer 35

1. Systematic Review (:
2. RCT
3. Cohort study
4. Case control
5. Cross sectional/survey
6. Case report
   7 Mechanistic studies
7. Editorial/ expert opinion

Question 36

Type 1 error does what

Answer 36

Rejects the null hypothesis when null hypothesis is true (false positive)
e.g Telling someone they have ACL tear when they do not
This is false positive b/c your fall is about what is true

Question 37

Type 2 error does what

Answer 37

Accepts null hypothesis when it is false (not true)
False negative

False either way cause its an error. This is false negative b/c its a double negative

e.g Telling someone they do not have an ACL year hen they do

Question 38

MCD vs MCID

Answer 38

MCID: Smallest change that would be important to patient
Thats why its minimal CLINICALLY important difference

MCD: smallest amount of change that can be detected and is reliable

50 meter change is MCID for 6MWT

Question 39

NNT

Answer 39

Number needed to treat to prevent one bad outcome

The ideal number is 1 (meaning each treatment is effective at preventing a negative outcome)

Question 40

Case studies

Answer 40

Are for describing a single phenonomenon