CDM Reliability (10/8b) [Integrative]

Question 1

Levels of Measurement

Answer 1

Nominal
Ordinal
Interval
Ratio

Question 2

Nominal Measurement

Answer 2

OVERVIEW

• names, nonnumeric data with no order or intervals
• EX: sex, insurance, names, disease/condition

DESCRIPTIVE STATS
- frequency, tallies, counts, percentage, mode

Question 3

Ordinal Measurement

Answer 3

OVERVIEW

• has order, no consistent intervals
• EX: numeric pain scale, poor/fair/good/etc.

DESCRIPTIVE STATS

• same as nominal
• central tendency: mode, median
• range

Question 4

Interval Measurement

Answer 4

OVERVIEW

• has order and equal intervals
• EX: time intervals, weight

DESCRIPTIVE STATS

• same as nominal and ordinal
• central tendency: mean
• variability: standard deviation, MDC

Question 5

Ratio Measurement

Answer 5

OVERVIEW

• has order and intervals, true zero
• EX: TUG time intervals, range of motion

DESCRIPTIVE STATS

• same as nominal and ordinal
• central tendency: mean
• variability: standard deviation, MDC

Question 6

Continuous Data Precision

Answer 6

Digital — important to know how much rounding was done

Analog — measure as precisely as we can to reduce rounding error; usually to the nearest ½ unit displayed

Heart Rate — can be really error prone

Question 7

Basic Relationship Between Measurement and Error

Answer 7

Measured value = true value + error

an estimate of actual value

Question 8

Types of Error

Answer 8

Patient
Examiner
Environment
Instrument

Question 9

Standard Error of Measurement (SEM)

Answer 9

estimate of the average variability expected around a measurement, how error is quantified

SEM = s√(1 - rxx )

Use SEM to determine CI around a measurement
95%CI = X ± ~2 * SEM , (X = measurement)

Question 10

Confidence in Single Measure (CiM)

Answer 10

—95% Confidence in measure (CiM 95)

Measurement ±1.96 * SEM

If wanted a 68% confident would use 1 SEM

Question 11

Minimal Detectable Change (MDC)

Answer 11

MDC provides more meaningful information than just reliability coefficients

—MDC95 = CiM95 x √2
MDC95= (1.96 x √2) * SEM
MDC95= 2.77 * SEM

Question 12

MDC Characteristics

Answer 12

SEM (estimate of the average variability expected around a measurement)

Based on:
- –Variability in patient performance
–- Variability in measurement process

–Specific to a patient population receiving the measurement

Question 13

MCID Characteristics

Answer 13

—Smallest change that would be important to patient

—Specific to a patient population receiving the measurement

Question 14

What do you need to calculate SEM?

Answer 14

Variability (s) of measures for a tested group

Reliability (r) coefficient for tested groups

Question 15

Reliability (r)

Answer 15

A value that quantifies the consistency of a tool, not accuracy

Necessary (but not sufficient) in order for a measure to be considered valid

Question 16

Test-Retest Reliability

Answer 16

Assumption that multiple measures of an unvarying characteristic should be equal

Question 17

SEMs and MDCs are ___ reliable than reliability coefficients like ICCs

Answer 17

more

Question 18

Intraclass Correlation Coefficient (ICC) - Equation

Answer 18

(Variability btwn subjects - Variability wthn subjects) / (Variability btwn subjects)

High Reliability = closer to 1
Low Reliability = closer to 0

Question 19

How variability affects ICC

Answer 19

To have a higher ICC (closer to 1)— need higher variability between subjects

This is a con about ICCs because they are very dependent on heterogeneity of the group

Higher variability within subjects leads to poor/low ICCs (closer to 0)

Question 20

Interrater vs Intrarater

Answer 20

Inter-rater = Between different raters, usually less consistent

Intra-rater or Test-Retest = Within a single rater, usually more consistent

Question 21

Reliability Quantified by

Answer 21

Reliability coefficient, such as ICC

SEM (standard error of measure)

–SEM is in the units of the measure

–Use SEM to calculate MDC

Question 22

Validity

Answer 22

does it measure what it says it measures?

Criterion

Construct validity established by comparing the measure to something else