Category Probability Curves - RC Syd

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Category Probability Curves

Transcript of Category Probability Curves - RC Syd

Category Probability Curves

Do you perform “activity”?

Do you have any difficulty performing “activity”?

no difficulty (5), to a little difficulty (4), moderate difficulty (3), and

extreme difficulty (2)

Are you unable to perform the activity because of poor vision (1)

How much does your vision interfere with reading?

How much difficulty do you have reading ordinary print in newspapers?

No difficulty at all................................................... 1

A little difficulty...................................................... 2

Moderate difficulty................................................. 3

Extreme difficulty................................................... 4

Stopped doing this because of your eyesight ....... 5

More difficult

VDA:

To what extent, if at all, does your vision interfere with your ability to…? (not at all =1; a little = 2; quite a bit = 3; a lot = 4)

NEI-VFQ:

How much difficulty do you have…? (no difficulty at all = 1; a little difficulty = 2; moderate difficulty = 3; extreme difficulty = 4; stopped doing

this because of your eyesight = 5)

ADVS:

Would you say that you… with? (No difficulty at all = 5; A little difficulty = 4; Moderate difficulty = 3; Extreme difficulty = 2; Cannot…)

Is it due to vision problems that you cannot… (Yes = 1; No = NA)

TyPE:

How much does your vision hinder, limit, or disable you in each of the following activities?

(not at all =1; a little bit =2; some =3; quite a lot =4; totally disabled =5; don’t do for other reasons =0)

CatSxScale:

Do you have difficulty……..? (No = 0; A little difficulty =1; A moderate amount of difficulty = 2; Very difficult = 3; Unable to do = 4

VF-14:

Do you have difficulty, even with glasses,…….? (Yes / No = 0 / Not applicable)

If yes, how much difficulty do you currently have?

(A little=1; A moderate amount=2; A great deal=3, Unable to do the activity=4) Less difficult

0.00

0.30

0.50

0.70

0.90

1.10

1.20

0.10

0.40

0.60

0.80

1.00

0.20

Pilot Instrument

Instructions

Demographics

Large number of items

Appropriate response scale

Administered to an appropriate population

Item Reduction from Pilot

Rasch analysis provides a powerful tool

for use in item reduction, to ensure

unidimensionality

| 15.3 | | | | | 2.0 | 16.3 | | 89.4 90.4 | 9.3 20.3 59.4 83.4 | 1.3 8.2 23.3 | 18.3 26.4 | 7.3 27.3 75.4 88.4 | 57.4 58.4 76.4 | 12.4 13.4 14.4 24.4 52.4 | 6.3 19.2 38.3 73.3 | 10.3 28.4 45.4 80.3 | 74.3 | 4.4 17.3 21.4 29.4 30.4 1.0 | 2.3 11.3 32.4 44.4 81.2 | 27.2 36.4 79.4 85.3 | 7.2 16.2 35.4 37.4 40.4 | 1.2 3.3 9.2 18.2 31.4 | 4.3 11.2 21.3 34.4 54.4 | 5.3 6.2 10.2 13.3 25.3 | 2.2 28.3 34.3 39.3 43.4 | 12.3 17.2 23.2 26.3 32.3 | 14.3 15.2 20.2 22.3 40.3 | 8.1 37.2 50.4 | 3.2 4.2 24.3 30.2 32.2 | 21.2 28.2 29.2 60.4 66.3 | 31.3 35.3 40.2 55.4 57.3 | 5.2 12.2 25.2 33.3 35.2 0.0 | 13.2 14.2 54.3 63.2 X | 11.1 34.1 42.3 56.3 61.2 | 7.1 19.1 22.2 26.2 33.2 XXX | 3.1 31.2 45.2 52.2 58.2 XXX | 18.1 27.1 46.3 54.2 65.3 XXXX | 1.1 24.2 35.1 59.2 68.2 XXXX | 32.1 33.1 41.3 47.3 48.3 XX | 17.1 36.2 43.2 44.1 50.3 XXXX | 9.1 10.1 38.1 40.1 42.2 XXXXXX | 2.1 51.3 65.2 75.3 78.1 XXXXXXXX | 6.1 39.1 41.2 55.3 57.2 XXXXXXX | 5.1 46.2 47.2 48.2 50.2 XXXXXXXXXXXXX | 14.1 29.1 31.1 45.1 49.2 XXXXXXX | 4.1 21.1 28.1 52.1 55.2 -1.0 XXXXXXXXXXXXXXXXXXXX | XXXXXXXXXXX | 30.1 41.1 43.1 51.2 XXXXXXXXXXXX | 25.1 36.1 48.1 49.1 66.1 XXXXXXXXXXXXXXX | 12.1 50.1 58.1 88.2 XXXXXXXXXXXXXXXXX | 16.1 26.1 55.1 60.1 XXXXXXXXXXXXXXXXXXX | 68.1 82.3 XXXXXXXXXXXXXXXXX | 22.1 23.1 47.1 51.1 69.1 XXXXXXXXXXX | 15.1 20.1 XXXXXXXXXXXXXXX | XXXXXXXXXX | 13.1 42.1 59.1 65.1 76.2 XXXXXXXXXXX | 56.1 70.1 XXXXXXXXXXXXX | 46.1 57.1 75.2 XXXXXXXXXXX | 64.1 XXXXXXXX | 77.2 86.1 -2.0 XXXXXX | 87.1 XXXXXXX | XXXX | XXXX | 24.1 XXXXXXXXX | XXX | 88.1 | XXX | X | 82.2 | X | XX | X | 84.1 89.1 -3.0 XX | 83.1 | | 76.1 XX | | 77.1 | X | XX | 75.1 | | | | | | -4.0 | | | 82.1 |

Item Reduction

Eliminate items which are too easy for

the subjects - analogous to ceiling effect

Eliminate items that are redundant

Eliminate misfitting (measuring

something else)

Eliminate items with large amounts of

missing data

Visual Disability Assessment

To rescale a conventional questionnaire, the Visual Disability Assessment* using Rasch analysis to create a linear measure of visual disability

To optimize item fit to the construct and to maximize targeting of item difficulty to cataract surgery patient ability

To assess the psychometric performance of the new questionnaire

* Pesudovs K, Coster DJ. Validation of a new tool for the assessment of subjective visual disability. Br J Ophthalmol. 1998;82:617-24.

The Visual Disability Assessment To what extent, if at all, does your vision interfere with your ability to carry out the following activities?

When you assess the level of visual interference, take into account both the degree to which you can perform the task as well as any extra effort involved.

Answer for both eyes, either not at all (1), a little (2), quite a bit (3), a lot (4) or answer not applicable (NA)

Reading NA 1 2 3 4

Seeing in the distance NA 1 2 3 4

Recognising faces across the street NA 1 2 3 4

Watching TV NA 1 2 3 4

Seeing in bright light / glare NA 1 2 3 4

Seeing in poor or dim light NA 1 2 3 4

Appreciating colours NA 1 2 3 4

Driving a car by day NA 1 2 3 4

Driving a car by night NA 1 2 3 4

Walking inside NA 1 2 3 4

Walking outside NA 1 2 3 4

Using steps NA 1 2 3 4

Crossing the road NA 1 2 3 4

Using public transport NA 1 2 3 4

Travelling independently NA 1 2 3 4

Moving in unfamiliar surroundings NA 1 2 3 4

Employment / housework activities NA 1 2 3 4

Hobbies / leisure activities NA 1 2 3 4

Results – item suitability

Several VDA items poorly contributed to

the measurement of visual disability –

redundancy or misfit

Items with fit statistics outside the range of

0.60 to 1.40 were eliminated

Items were, on the whole, too “easy” for

participants

Using fit statistics +--------------------------------------------------------------------------------------+

|ENTRY RAW | INFIT | OUTFIT |PTMEA| |

|NUMBER SCORE COUNT MEASURE ERROR|MNSQ ZSTD|MNSQ ZSTD|CORR.| Items |

|------------------------------------+----------+----------+-----+---------------------|

| 1 576 243 40.48 .80| .98 -.2|1.13 1.1| .71| reading |

| 2 479 243 46.88 .83| .80 -2.3| .72 -2.2| .71| seeing distance |

| 3 506 237 44.17 .82| .98 -.2| .87 -1.1| .71| recognising faces |

| 4 404 241 52.24 .92| .88 -1.2| .99 .0| .61| watching TV |

| 5 611 243 38.25 .80|1.26 2.7|1.55 4.1| .68| seeing bright light |

| 6 540 243 42.80 .80|1.24 2.5|1.43 3.2| .64| seeing poor light |

| 7 308 243 63.63 1.31|1.62 3.4|2.79 4.5| .35| appreciating colors |

| 8 262 133 45.14 1.13| .98 -.1| .78 -1.2| .70| driving by day |

| 9 378 126 29.07 1.17|1.09 .7|1.69 3.1| .77| driving by night |

| 10 276 240 69.91 1.71|1.07 .4| .63 -1.0| .39| walking inside |

| 11 343 240 58.10 1.08| .95 -.3| .74 -1.2| .55| walking outside |

| 12 370 240 55.20 .99|1.01 .1| .85 -.8| .57| using steps |

| 13 377 238 54.00 .97| .80 -1.9| .67 -2.0| .62| crossing road |

| 14 270 184 55.65 1.20| .89 -.7| .60 -1.9| .59| public transport |

| 15 319 229 58.64 1.14| .89 -.8| .62 -1.8| .55| travel independently|

| 16 367 235 54.26 .98| .87 -1.2| .67 -2.0| .60| unfamiliar surround |

| 17 347 238 57.00 1.06|1.04 .3| .86 -.6| .53| employment/housework|

| 18 460 234 46.54 .85|1.40 3.8|1.42 2.7| .59| hobbies |

|------------------------------------+----------+----------+-----+---------------------|

| MEAN 400. 224. 50.66 1.03|1.04 .3|1.06 .2| | |

| S.D. 103. 36. 9.60 .23| .21 1.7| .54 2.2| | |

+--------------------------------------------------------------------------------------+

Visual Disability Assessment Items │ Patients

<easier>│<more disabled>

│ BILAT

│ COMORB UNILAT

70 walking inside ┼T BILAT

│ COMORB BILAT

appreciating colors T│

│ BILAT

│ COMORB BILAT

60 ┼S COMORB BILAT (3) COMORB PPHAKE COMORB UNILAT

walking outside travelling independently │

employment/housework │ BILAT COMORB UNILAT (2)

public transport using steps │ BILAT (3) COMORB UNILAT (3)

unfamiliar surroundings crossing road │ BILAT COMORB BILAT (5) COMORB UNILAT

watching TV │ BILAT (2) COMORB BILAT (2)

S│ BILAT (3) COMORB BILAT (2) COMORB PPHAKE COMORB UNILAT (2) UNILAT

50 ┼M BILAT (4) COMORB BILAT (2) COMORB UNILAT UNILAT

│ BILAT COMORB BILAT (5) COMORB UNILAT (2) UNILAT

seeing distance hobbies │ BILAT (3) COMORB BILAT (4) COMORB PPHAKE COMORB UNILAT (3)

driving by day │ BILAT (2) COMORB BILAT (5) COMORB PPHAKE COMORB UNILAT (4)

recognising faces │ BILAT (6) COMORB BILAT (2) COMORB UNILAT PPHAKE

seeing in poor light │ BILAT (7)COMORB BILAT (2) COMORB UNILAT (4) UNILAT (3)

│S COMORB UNILAT UNILAT (2)

40 reading ┼ BILAT (3) COMORB BILAT (2) COMORB PPHAKE COMORB UNILAT (3) UNILAT (2)

seeing in bright light M│ BILAT (2) COMORB BILAT COMORB PPHAKE COMORB UNILAT UNILAT (2)

│ COMORB BILAT (5) COMORB UNILAT

│ BILAT COMORB BILAT (2) COMORB UNILAT (3) UNILAT (2)

│ BILAT COMORB BILAT (2) COMORB UNILAT (3) UNILAT (5)

│ BILAT (2) COMORB PPHAKE COMORB UNILAT (2) UNILAT (8)

│T BILAT (2) COMORB BILAT COMORB UNILAT UNILAT (4)

30 ┼ BILAT (2) COMORB BILAT COMORB PPHAKE (2) COMORB UNILAT (4) PPHAKE (2) UNILAT (3)

driving by night │ BILAT COMORB UNILAT UNILAT (4)

│ COMORB PPHAKE UNILAT (6)

S│ COMORB PPHAKE (3) COMORB UNILAT (2) PPHAKE UNILAT (3)

│ PPHAKE

│ COMORB PPHAKE (3) PPHAKE (3) UNILAT (4)

20 ┼

│ BILAT COMORB UNILAT (3)

│ COMORB PPHAKE

│ COMORB UNILAT (2) PPHAKE (4) UNILAT (2)

T│

│ COMORB UNILAT PPHAKE (3) UNILAT (5)

10 ┼ COMORB PPHAKE (6) PPHAKE (19) UNILAT (2)

<harder>│<less disabled>

Unidimensionality

Factor analysis or principal components

analysis (PCA)

Identify groupings of items which form

additional dimensions

Useful tool for creating dimensions of

measurement

Differential Item Functioning

Rasch analysis insight into the

performance of the instrument in

population subgroups

Performs a separate analysis in sub-

groups and compares calibrations

Important for population demographics,

different locations, different disease

groups etc

Conclusion

Design

Content

Rating scale

Scoring

Validity

Reliability

Interpretability