Approaches to Assessing and Correcting for Bias in Distributions of Cognitive Ability due to Non-Response David R. Weir Jessica D. Faul Kenneth M. Langa Health and Retirement Study

Why focus on cognition? Surveying the cognitively impaired population is difficult In contrast to income or physical health, which may affect participation but for which there is no strong theoretical reason for a particular direction of bias, Surveys are complex conversations that require cognitive ability to participate The cognitively impaired will be less likely to participate or even excluded from participation

So what? Cognitive impairment is the most important reason for long-term care Burden on families Cost to society Measuring it, and its effects, accurately is a crucial aim of “HRS” surveys

Attrition and non-response Baseline cross-section may underrepresent impairment Could get worse over time as newly impaired drop out There are ways to minimize this but they are not always used

Outline Compare HRS and ELSA non-response Compare HRS and ELSA bias in cognition due to non-response Further examine HRS Panel data on cognition and non-response Linked Medicare claims to test for bias not evident in panel observations (occurring after last interview taken)

Non-response, NOT attrition Attrition means permanent departure from sample –Mortality? –No, if our samples did not have mortality they would be extremely UNrepresentative! –Both HRS and ELSA have mortality similar to population life tables Permanent removal from sample is a somewhat arbitrary definition/decision We focus on non-response of all survivors

Cognition and mortality Mortality rates are higher for those with low cognition, controlling for other things These differentials are similar in HRS and ELSA

Mortality by Cognition, ELSA and HRS (mortality ratio age-adjusted)

Response Rate of Survivors at Follow- up Waves (Age-eligible at baseline), ELSA and HRS

Response Rate of Survivors at Follow- up Waves (Age-eligible at baseline), ELSA and HRS (excluding proxies)

Non-response Non-response much higher in ELSA than in HRS More than twice as much Smaller difference when proxies are excluded from HRS What about bias?

How to assess bias in cognition measurement due to non-response? One approach: use baseline measure Compare baseline cognition level of respondents at follow-up wave to baseline level of all survivors to that follow-up wave If non-response in unrelated to baseline cognition, there would be no difference Difference between them measures the bias Given the correlation of cognition and survival, must exclude decedents at each follow-up wave because that is not bias

Bias in Cognition at Follow-up (Unweighted), ELSA and HRS

Non-response and bias ELSA had about twice the rate of non- response as HRS Nearly four times the bias in cognition Why? ELSA also had stronger correlation of cognition and non-response

Non-response by Cognitive Score at Prior Wave, ELSA and HRS

Non-response by Cognitive Score at Prior Wave, ELSA and HRS with and without proxy interviews

Proxy interviews Without proxy interviews, HRS bias in cognition from non-response would look very similar to ELSA

Bias in Cognition at Follow-up (Uneighted), ELSA and HRS (excluding proxies)

Proxy Interviewing Eliminates Most of the Bias in Cognition from Non-response

What about sample weights? Weights are the primary option available to surveys to correct for bias in non-response Do the current sample weights in HRS and ELSA correct the non-response bias in cognition?

Bias in Cognition at Follow-up (Weighted), ELSA and HRS

Effect of weights For ELSA, sample weights eliminate about half the bias in cognition due to non- response

Why are weighted numbers worse for HRS (especially AHEAD)? HRS weights give zero weight to nursing home residents Undoes some of the advantage of proxy interviewing HRS now has capacity to produce weights for nursing home residents

Percent in Nursing Homes, by Age, 2006: American Community Survey and HRS

HRS represents well the nursing home population So unweighted numbers (including nursing home residents) should be close to weighted numbers when weights for nursing home residents are included

Comparison of bias in AHEAD cohort in 2000 and 2002 with and without nursing home weights

Proxy Reporting Crucial to Representing the Cognitively Impaired in Surveys From the proxy we can capture their costs, impact on family,… What about their cognition? Proxy/informant reports can be useful for ascertaining dementia But not easily comparable to scores on cognitive testing  Need a crosswalk between observed cognition and proxy reporting

HRS and ADAMS HRS uses Jorm IQCODE with proxies Ideally, we’d want HRS cognitive scores and Jorm scores on the same people In HRS, get one or the other Next-best: have some good third measure available for both  ADAMS has many such measures

ADAMS Clinical Dementia Rating Scale, by HRS Jorm IQcode

ADAMS Clinical Dementia Rating Scale, by HRS Cognition Score

Crosswalk can be established Combine proxy and self-reports in HRS Track overall cognitive health Robust to whether interview done by proxy or self Can use combined data in longitudinal model of non-response by cognition

Logistic regression of non-response at wave t, by age and cognition at wave t-1 (combining self-IWs and proxies)

So, why worry? Selection bias at survey baseline Cognitive change between waves may be related to rates of non-response  Use information external to the survey

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