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Scaling Session.

Scaling Session

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Scaling Session

Measurement implies assigning numbers to objects or events. In our case, the numbers “weight” responses to questions, so that saying “Yes” to a question on being able to walk out of doors will receive a particular numerical score, instead of merely counting as one “Yes” reply.

Where do these numbers come from?

- You can assign arbitrary weights
- You can estimate weights from a judgment task
- Copy them from the literature
- Measure weights through a scaling task; scaling is concerned with how to select appropriate numbers to represent amounts of health
- Infer weights from administrative, legal, or social decisions

- Most weights come from scaling tasks
- Scaling is undertaken by people who are asked to perform a scaling task; this measures their preferences for specified health states
- These preferences can be divided into values and utilities
- Two contrasting historical traditions have influenced the way we assign numbers in health measurement: psychometrics and econometrics

- Psychometrics deals with feelings and perceptions, and is appropriate in judging single items; it measures values.
- The econometric tradition derives from studies of consumption and choice between goods, so focuses on making decisions under conditions of uncertainty; it measures choice given risk.
- “Utilities are the numbers that represent the strength of a person’s preferences for particular outcomes when faced with uncertainty” (George Torrance)

- Hence the econometric approach is suitable for weighting health states for clinical decision analysis and the patient’s choice of therapy, planning care & anything to do with future health around which there is uncertainty.
- The psychometric approach is good for valuing current health states.
- In general, utility scores are higher than value judgments

Many variants. For example:

- Thurstone “equal-appearing interval scaling.” Cards with descriptions of health states (the items) written on each; raters place these on scale representing intensity of the relevant concept (e.g., disability). Typically 15 spaces on scale; item weights from median of individual judgments. High SD suggests ambiguous item
- Magnitude estimation. Raters compare the health states with a standard state and are asked to provide a number or ratio indicating how much worse or better each is than the standard.

- Standard Gamble. Respondent chooses between certain outcome (e.g., living in the restricted health state for 10 years and then dying) and a gamble (e.g., 90% chance of immediate cure, but with a 10% chance of immediate death). The more severely they judge the current state, the higher the risk of death they will accept to avoid it.
- Time trade-off. Respondent asked to imagine being in the health state and is then asked how many years of life hw will give up to be cured from it.

Psychometric

- Paired comparisons method
- Equal-appearing interval scaling
- Likert scaling
- Magnitude estimation methods
Utility Methods

- Standard gamble
- Time tradeoff
- Willingness to pay

- Choose people to make the judgments
- Choose the health states to be rated
- Select a preference measurement method
- Collect the preference judgments
- Analyze the results and assign weights to each health state

* Half p for that category plus p for category below

1 2 3 4 5 6

I can run a mile TX X X X X

I can do the grocery shopping T T X X X X

I can walk one block TT TX X X

I can rise from an armchair TT T T X X

I can use the toilet without assistance T T T T T X

score 5 4 3 2 1 0

- Is it worth the effort? The weighted and unweighted versions of many health measures often correlate +0.90 and over.
- The overall score in any scale is weighted by number of items included in each sub-section.
- Think about unidimensionality. Is “independence” unidimensional?
- Sensibility of overall scores: should we add incontinence to mobility?
- Is Hi + Lo equivalent to Med + Med?

- Note that numerical ratings can represent many different aspects of a health state:
- occurrence of an attribute (e.g., symptom)
- probability it will occur
- undesirability of the attribute
- utility (or undesirability, given its probability)

- Do interval scales represent conceptually equal intervals?