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25 Cards in this Set

  • Front
  • Back
- numerical scale indicate a classification

- inclusion in one category is not better/worse, larger/smaller, etc. than another

- no proportionality
Nominal Examples
- male/female

- number on athlete's uniform

- 1=OA, 2=RA, 3=Normal

- Yes/No

- Agree/Disagree
- order or rank

- comparison of better than or greater than can be used

- no proportionality
Ordinal Examples

- Pain Scale

- Finish in a race

- Likert scale (faculty evals)
- equal intervals between numbers, but not related to absolute zero

- all "made up" scales

- some proportionality
Interval Examples
- IQ

- Fahrenheit

- Centigrade

- Calendar Years

- Gymnastics score
- highest level of measurement

- contains all characteristics of other three scales

- absolute zero
Ratio Examples

- Height

- Weight

- Force

- Kelvin temp
1) How high you jump

2) Massed group or distributed group?
1) Ratio

2) nominal
1) Right vs Left handed?

2) Score of a diver (swimming)?
1) nominal

2) Interval
Goni measurement of shoulder
1) Isokinetic test

2) time to run a mile
1) ratio or interval

2) ratio
o Each member of population has an equal chance of being selected
o Put all names in a hat and “draw”
o Table of random numbers
o Become cumbersome with large populations
simple random sampling
o Pick every nth person from a list
o Requires a list of subjects
o Ex. – choose every 10th name from a list of 1000 subjects; n = 100
systematic sampling
o Used when a certain subgroup must be represented in adequate number
o Must identify stratifying characteristic
stratified sampling
o Frequently used in PT research
o Due to limited funding
non-probability sampling
o Use of readily available subjects
o Consecutive sampling – recruit patients as they become available
o Volunteers
o Most common sampling technique used in PT research
o Problem – Self Selection
 We do not know what attributes are present in those who volunteer compared with those who do not
 Age, Motivation, Activity Level
sample of convenience
o Researchers identify a few subjects who are then asked to identify other potential members
o Ex. – study of patients (ACL) who all return sports activities prior to recommendation
o These subjects may be able to identify others
snowball sampling
o Hand picking of subjects based on specific criteria
o Not based on availability (convenience)
o Ex. – to test a ROM measurement tool you may specifically pick people with a variety of ROM impairments.
purposive sampling
o Use table of random numbers
 Ex. – 32 subjects; 4 groups; First 8 go into group 1, Next 8 into group 2, etc.
random assignment by block
o Count off
o Frequently used
o Ex. – 32 subjects; 4 groups; Count off 1 through 4
systematic assignment
o Subjects are matched on important characteristics
o These subgroups are randomly assigned
o Similar to stratified sampling
o Ex. – 32 subjects; 4 groups; divide into male/female subgroups; then assign to groups (ex. – count off); Ensures relatively equal distribution of sex
matched assignment
advantages and disadvantages of matched assignment
o Advantage: ensures equal distribution in variables that are matched (sex)
o Disadvantage: other characteristics may not evenly distribute (age, etc)
o Ex. – comparison of 4 post-surgery protocols
o As they enter study after surgery, they are put in next available group
consecutive assignment
 One measurement should not precede second measurement in any systematic method
 Especially when measurement is separated
random ordering