Questionnaire Dwelling Unit-Level and Person Pair-Level Sampling ...

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B.1.1 Person Level B.1.1.1 Receiving and Deriving Person-Level Poststratification Control Totals Civilian, noninstitutionalized population estimates for ages 12 or older were provided by the Population Estimates Branch of the U.S. Bureau of the Census. We received two files, one at the national level and the other at the State level, each containing estimates of the population broken down by levels of month (12 levels), Hispanicity (2), race (6), sex (2), and age (11). The breakdown received from the census did not match the levels of the domains that we wanted to control. To account for this, we collapsed levels. From this altered data, we created datasets with model group-specific control totals. Observations in these datasets corresponded to a breakdown by quarter (4), Hispanicity (2), race (5), sex (2), age (11), and number of States 26 in the model group (number of States varied according to which census region was represented in the model group). B.1.1.2 Adjusting SDU Data to the Control Totals In the person-level weighting, the SDU weights were poststratified to meet control totals based on the population estimates received from the census. For NSDUH weighting, GEM was utilized to calibrate sample weights to multiple control totals. In doing so, each SDU received an adjustment factor, which, when multiplied by the initial weight, produced a final weight. The sum of all final weights corresponded to the civilian, noninstitutionalized population estimate for ages 12 or older, and the sum of all final weights in a domain corresponded to the control total for that domain. Note that there were a number of controls being calibrated to for each SDU, depending upon the domains to which the SDU belonged. The adjusted SDU weight reflected the civilian, noninstitutionalized population estimates for ages 12 or older and could be utilized as a basis for constructing controls at the QDU and person pair levels. B.1.2 QDU Level B.1.2.1 Deriving QDU-Level Poststratification Control Totals from Adjusted SDU Weights Since there were no controls for QDU-level poststratification available directly, we used the adjusted SDU weights. For these weights to be applicable at the QDU level, the SDU-level data had to be restructured by sorting and summing over the domains to be used in the QDUlevel calibration. This provided a dataset where the summed weight, which still added up to the proper population, was available for every domain to be utilized in the QDU calibration and thus could be used as a control total. 26 The District of Columbia is included among States. B-4
B.1.2.2 Adjusting QDU-Level Data to the Control Totals As was done for the SDU data, the QDU-level data was adjusted via calibration in GEM of sample weights to multiple control totals. Each QDU received an adjustment factor, similar to that described for the SDU weight in B.1.1.2. The controls utilized in this calibration were based on the SDU weight as described in B.1.2.1 above. The adjusted weight was representative of the civilian, noninstitutionalized population estimates for ages 12 or older for all domains controlled within the modeling. B.2 Derivation of Person Pair-Level Poststratification Controls B.2.1 Deriving Person Pair-Level Poststratification Control Totals from Adjusted SDU Weights and Household-Level Person Counts Analogous to the QDU weights, some of the person pair controls were based on the SDU weights. However, two sets of control totals were utilized in the modeling, with one set based on the SDU weights and the other set based on the questionnaire roster. For most pair data domains—those other than the 10 pair domains based on relationship—the control totals for the poststratification adjustments were obtained from SDU data and were based on the number of possible pairs within SDUs. In order to obtain these pair counts belonging to various sociodemographic domains, the screener roster information was used to calculate all possible pairs within SDUs. For example, consider an SDU with two persons aged 12 to 17 and three persons aged 26 to 34. From this household composition, one can construct one pair of persons aged 12 to 17, three pairs of persons aged 26 to 34, and six pairs of persons aged 12 to 17 and 26 to 34. It follows that the total number of possible pairs in this SDU is 10, from which the number of pairs belonging to the domain of interest can be obtained. On the other hand, for the 10 selected pair domains based on relationship, the control totals for the poststratification adjustments were obtained from the questionnaire roster. This involved calibrating the pair weights to the number of persons in households belonging to each domain of interest. These controls were obtained from the larger sample of singles and pairs (i.e., one or two persons selected from dwelling units) and were calculated at the QDU (household) level. The pair weights were adjusted by the appropriate multiplicity. See Section 6.3 for details on the multiplicity counts and Section 6.4 for details on the household-level control totals, which are referred to as household-level person counts. B.2.2 Adjusting Person-Pair Level Data to the Control Totals Like the SDU- and QDU-level data, the person pair-level data was adjusted via GEM. The use of two different types of controls required a minor modification to the GEM macro so that both sets of controls might be addressed simultaneously. Similar to the SDU- and QDUlevel poststratification steps, each pair received an adjustment factor, which, when multiplied by the initial weight, produced a final weight. The sum of all final weights corresponded to the civilian, noninstitutionalized population estimate for ages 12 or older, and the sum of all final weights in a domain corresponded to the control total for that domain. B-5
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2006 NATIONAL SURVEY ON DRUG USE AN
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Preface This report documents the m
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Table of Contents Chapter Page Pref
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Table of Contents (continued) Appen
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List of Tables Table Page Table 1.1
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List of Tables (continued) Table Pa
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List of Exhibits Exhibit Page Exhib
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CBSA DU ev GEM Half step Household-
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1. Introduction Traditionally, most
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produced a priori. It was anticipat
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to perform some treatment (such as
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P hij ( ) ⎡P P ⎤⎡ 1 1 ⎤ hi
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The QDU selection probability was d
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3. Brief Description of the General
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4. Predictor Variables for the Ques
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Exhibit 4.1 Definitions of Levels f
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Exhibit 4.2 Definitions of Levels f
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e. Youth Only; f. Young Adult Only;
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6. Editing and Imputation of Pair R
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from other pair members was sometim
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Table 6.1 Levels of the Variable PA
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Table 6.3 Measures of the Quality o
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identified pair member "A" as "othe
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performed at the household level ra
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pair member's roster and another pa
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Table 6.6 Age Group Pair Number Age
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13. MSA (metropolitan statistical a
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different ways depending upon the a
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5. parent-child (child 12 to 17), p
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ecause, even though the parent-chil
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Page 69 and 70: with children) lived within the hou
Page 71 and 72: 6.4.1.2 Sibling-Sibling Domains Whe
Page 73 and 74: 4. The respondent had a child and a
Page 75 and 76: parent-focus and child-focus counts
Page 77 and 78: the random imputation described ear
Page 79 and 80: 6.4.3.3.3 Spouse-Spouse Counts For
Page 81 and 82: 7. Weight Calibration at Questionna
Page 83 and 84: Exhibit 7.2 Summary of 2006 NSDUH P
Page 85 and 86: Table 7.1 Model Group QDU Sample Si
Page 87 and 88: 7.2.5 QDU Weight Component #15: Res
Page 89 and 90: 8. Evaluation of Calibration Weight
Page 91 and 92: 8.5 Sensitivity Analysis of Drug Us
Page 93 and 94: Table 8.2a Percentages of Youths (1
Page 97 and 98: Table 8.4 Percentages of Youths (12
Page 103 and 104: References Ault, K., Aldworth, J.,
Page 105: Singh, A., Grau, E., & Folsom, R.,
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Page 110 and 111: A.2 GEM Adjustments for Extreme-Val
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Page 120 and 121: C-2
Page 122 and 123: To help understand what effects wer
Page 124 and 125: Exhibit C.1 Definitions of Levels f
Page 126 and 127: C.3 How to Interpret Collapsing and
Page 128 and 129: The number of respondents in that c
Page 130 and 131: Exhibit C.2 Covariates for 2006 NSD
Page 132 and 133: C-14
Page 134 and 135: Table C.1b 2006 Distribution of Wei
Page 136 and 137: Exhibit C.1.1 Covariates for 2006 N
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Page 148 and 149: C-30
Page 156 and 157: C-38
Page 164 and 165: D-2
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D-4
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E-2
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E-4 Table E.1 2006 NSDUH Selected Q
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E-6 Table E.2 2006 NSDUH Respondent
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F-2
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Table F.1 2006 NSDUH QDU-Level Slip
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G-2
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G-4 Table G.1 2006 NSDUH Selected Q
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G-6 Table G.2 2006 NSDUH Respondent
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H-2
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Exhibit H.1 Definitions of Levels f
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Exhibit H.2 Covariates for 2006 NSD
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H-8
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Table H.1b 2006 Distribution of Wei
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Exhibit H.1.1 Covariates for 2006 N
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H-16
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H-18
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Table H.2b 2006 Pair Weight GEM Mod
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H-26
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I-2
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Table I.1 2006 NSDUH Person Pair-Le
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J-2
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J-4 Table J.1 Domain 2006 NSDUH Sel
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J-6 Table J.2 2006 NSDUH Respondent
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J-8 Table J.3 Domain 2006 NSDUH Res
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J-10
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K-2
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Table K.1 2006 NSDUH Respondent Pai
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L-2
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L-4 Table L.1 2006 NSDUH Selected P
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L-6 Table L.2 2006 NSDUH Respondent
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L-8 Table L.3 2006 NSDUH Respondent
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L-10 Table L.3 2006 NSDUH Responden
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M-2
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procedures were implemented indepen
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first sorting variables). In genera
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predicted mean(s), the neighborhood
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N-2
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The PMM method is only applicable t
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type of constraint, called a "logic
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N-8
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O-2
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Table O.1 Rules for Determining Mat
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Table O.1 Rules for Determining Mat
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O-8 Table O.2 Priority Condition Ru
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O-10 Table O.2 Priority Condition 2
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Table O.2 Priority Condition Rules
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P-2
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P-4 Table P.1 Priority Condition, F
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Table P.1 Priority Conditions Used
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P-8 Table P.1 Priority Condition, F
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P-10 Table P.2 Priority Condition,
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P-18
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Q-2
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data, which was adjusted to more re
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Table Q.1 Model Group 3 (15-17, 15-
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Table Q.1 Model Group 9 (18-20, 26+
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Table Q.2 Pair Domain Sibling (12-1
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Table Q.3 Model Group Parent- Child
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Table Q.3 Pair Domain Spouse- Spous
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Table Q.4 Pair Domain Sibling (12-1
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Q-18
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R-2
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was not imputed, the indirect count
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1. The counts disagreed if a househ
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S-2
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with parent(s) in the household) fo
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• Both had counts of children wit
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− The other conditions had not al
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• The number of children in the s
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5. Two family units might be in the
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− − No bad relationship codes i
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elationship codes, and the sum of t
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• The pair relationship was not a
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• The screener count of roster me
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15. The count of the number of spou
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member had a spouse-spouse-with-chi
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• If the spouse-spouse counts exc
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• The number of roster members yo
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