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Design of the sampling frame of the 2008 French survey on disability and health INSEE Loic Midy.

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Presentation on theme: "Design of the sampling frame of the 2008 French survey on disability and health INSEE Loic Midy."— Presentation transcript:

1 design of the sampling frame of the 2008 French survey on disability and health INSEE Loic Midy

2  Problem to solve: How can we get a high number of people with disability in the sample of our survey?  Our solution: we do a two phase survey: –Step 1: we did in 2007 a short survey called VQS on 140 000 households –Step 2: we classify VQS respondants into stratums of assumed severity of disability –Step 3 : the sample of the disability survey (size 39 000) is a stratified sampling on those stratums

3 This methodology will be of good quality only if all the 3 steps have themselves a good quality. This raises 3 issues tackled in this presentation  Issue 1 (linked to step 1): how should we design the short set of questions of VQS in order to detect people with disability?  Issue 2 (linked to step 2): how should we do the classification of VQS respondants into stratums of severity of disability?  Issue 3 (linked to step 3):what rules should the stratified sampling of the disability survey follow?

4 Issue 1: design of VQS questions Global philosophy: disability\handicap is a multi dimensionnal issue. Backed by a study of the 1999 VQS data on the people aged 16 or more: 2,4% persons declared a global limitation for 6 months or more but not a single functionnal limitations (7 questions). 13,3% persons declared a least one functionnal limitation but no global limitation for 6 months or more. 14% of the persons who have an official recognition of a disability\ handicap don’t think they have a disability\ handicap !!!

5 Issue 1 (2) Dimensions included in the 2007 VQS  Questions on health (mini module 1 and 2)  Question on limitation (mini module 3)  Questions on functionnal limitations  Questions on help (human, technical, and housing adaptations)  Question on self perception of handicap  Question on official recognition of handicap

6 Issue 1 (3) the intellectual and psychical handicap were not well detected with the 1999 VQS questions: 48% of HID respondants who declared that they often put themselves in danger answered NO to all 1999 VQS questions. 63% of HID respondants who declared that people often reproached them to be to agressive or to impulsive answered NO to all 1999 VQS questions.

7 Issue 1 (4) => we added 4 questions to detect those handicap. Those 4 questions where asked in another survey on adults asking an official recognition of handicap where the real impairment is available (coded by a general practitionner using the medical files)

8 Issue 1 (5) questionsIntellectual impairment Psychical impairment sensibi lity specifi city sensibi lity specifi city Concentration0,540,590,580,64 Memory0,590,500,620,53 initiatives0,680,610,600,65 Problem solving0,720,650,540,67 A least one positive answer 0,870,330,840,37

9 Issue 2 We used 2 methods to classify VQS respondant: One is based on a score The second is a mixed classification

10 Issue 2: score Principle:  A note is assigned to each answer. Ex: question How is your health in general –Answer very bad=>5 points –Answer bad=>3 points  Final score for a person=(sum of note)\ (maximum sum of note)*100 => partial non response taken into account  Allocation of each person to a stratum according to his score (ex: if score>80 => stratum 4). –Arbitrary threshold –OR hierachical classification on a sample of persons on variable final score

11 Issue 2 (2) How can we assign a weight to each answer? In 1999 we had a VQS survey and then a disability survey called HID. We detect the VQS 1999 questions explaining the best one HID variable by a logistic regression => Gives an idea of the most important VQS questions BUT not perfect nor complete because VQS 1999 and VQS 2007 are not all the same (questions added, deleted, reformulated)

12 Issue 2 : mixed classification The steps are:  Basic imputation on missing data : non response => imputation answer NO.  Analysis of multiples correspondancies (ACM)  Classification (mobile centers méthod: SAS: FASTCLUS) on the firsts axes of the ACM=> 10 000 clusters  Hierarchical classification (SAS: CLUSTER) on the 10 000 clusters

13 Issue 2 (2): comparisons (temporary data)

14 Issue 3  what rules should the stratified sampling of the disability survey follow?  We have 4 stratums of severity of handicap from 1 (no handicap at all) to 4 (important handicap).  We sample 100% of people in stratum 4. The main question is which percentage of people should we sample in stratum 1?

15 Issue 3 (2) We should estimation confidence interval on variable of interest to answer BUT is this case the calculus are very difficult=> study of the dispersion of the weight.

16 Estimation for 2008 disability survey (temporary data) Data from the 1999 disability survey Quantile Estimate of weights 100% Max 12688100% Max 59430 99% 823599% 41879 95% 645795% 31627 90% 559090% 3997 75% Q3 386175% Q3 1334 50% Median 136950% Median 690 25% Q1 50025% Q1 384 10% 29310% 188 5% 2215% 110 1% 1031% 51 0% Min 290% Min 28


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