ON THE USE OF HIERARCHICAL MODELS

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Transcription:

ON THE USE OF HIERARCHICAL MODELS IN METHOD COMPARISON STUDIES Alessandra R. Brazzale LADSEB-CNR alessandra.brazzale@ladseb.pd.cnr.it TIES 2002 Genova, June 18-22, 2002 1

Credits Alberto Salvan (LADSEB-CNR, LIA-ISS) Stefano Roletti (ARPA-Piemonte) SETIL study Funding: AIRC, MIUR TIES 2002 Genova, June 18-22, 2002 2

Outline 1) Background a) The SETIL project b) The EMDEX calibration data 2) Hierarchical modeling approach Applied to the EMDEX calibration data 3) Conclusion, discussion & ongoing research TIES 2002 Genova, June 18-22, 2002 3

The SETIL project epidemiological multi-centric case-control study investigates risk factors for childhood leukemia, non-hodgkin s lymphoma and neuroblastoma residential exposure to ELF-MF TIES 2002 Genova, June 18-22, 2002 4

Study protocol 1 Material: EMDEX dosimeters (Enertech Consultants Ltd., USA) 1) spot measurements: EMDEX II 2 2) long-term exposure: EMDEX Lite TIES 2002 Genova, June 18-22, 2002 5

Technical specifications RMS dosimeters EMDEX II : range : 0.01-300 µt accuracy : 1% (± 0.01 µt) EMDEX Lite : range : 0.01-70 µt accuracy : 2% (± 0.01 µt) TIES 2002 Genova, June 18-22, 2002 6

Questions of interest Are the instruments used reliable? Do the two instrument types agree? method comparison studies (approximate & gold standard) [Lewis et al., 1991] TIES 2002 Genova, June 18-22, 2002 7

Calibration study Helmholtz coil facility [Borsero et al., 2001] TIES 2002 Genova, June 18-22, 2002 8

Study design 23 EMDEX II, 20 EMDEX Lite meters nominal values: 0.1, 0.2, 0.4, 0.8, 1.0 µt (50 Hz) true MF density derived from current measurements in turn one of the three sensing coils pointed in the direction of the MF vector two sessions resultant + orthogonal projections TIES 2002 Genova, June 18-22, 2002 9

Study design (cont.) data record name matr coil hz B.g x y z B.m date time "EMDEX LITE" 104430 1 50 0.11 0.11 0.03 0.01 0.11 "17/08/01" 12.45 TIES 2002 Genova, June 18-22, 2002 10

Method comparison studies Two main approaches do not apply to our case! 1. Bland & Altman (1986) graphical representations measures of agreement 2. Lewis et al. (1991) one-way random-effects model intra-class correlation coefficient TIES 2002 Genova, June 18-22, 2002 11

Hierarchical modeling approach linear mixed-effects models with nested random coefficients [Goldstein, 1995] widely used to describe relationships between variables that are grouped according to one or more classification factors also used to model interactions between covariates associated with random effects TIES 2002 Genova, June 18-22, 2002 12

The EMDEX calibration data TIES 2002 Genova, June 18-22, 2002 13

The EMDEX calibration model Baseline formulation d ijkm = α + βx ijkm + σ ij ε ijkm d ijkm = B.m ijkm B.g ijkm x ijkm = B.g ijkm ε ijkm ~ N(0,1) i=1,2 (type), j=1,2,3 (coil orientation) k=1,,43 (serial number), m=1,2 (session) TIES 2002 Genova, June 18-22, 2002 14

The EMDEX calibration model (cont.) Extension d ijkm = (α + a i + a ij + a ijk ) + (β + b i + b ij + b ijk ) x ijkm + σ ij ε ijkm 1. (a i,b i ) ~ N(0,Σ 1 ) 2. (a ij,b ij ) ~ N(0,Σ 2 ), indip. 3. (a ijk,b ijk ) ~ N(0,Σ 3 ) σ ij = σ x ijkm δ ij TIES 2002 Genova, June 18-22, 2002 15

The EMDEX calibration model (cont.) Interpretation E[B.m ijkm ] B.g B.g ijkm ijkm α = β α: systematic error component β: relative measurement error conditional expectations TIES 2002 Genova, June 18-22, 2002 16

The EMDEX calibration model (cont.) Model fit maximum likelihood (REML), BLUP conditional t-tests and F-tests variance function random effects fixed effects R library nlme [Pinheiro & Bates, 2000] SAS PROC MIXED [SAS Institute Inc., 2001] TIES 2002 Genova, June 18-22, 2002 17

Results Final model d ijkm = (a i + a ijk ) + (β + b ij + b ijk )x ijkm + σ i ε ijkm a i ~ N(0,σ 2 a ), b ij ~ N(0,σ 2 b ) (a ijk,b ijk ) ~ N(0, diag[σ 2 aa, σ bb2 ]) i=1,2 (type), j=1,2,3 (coil orientation) k=1,,43 (serial number), m=1,2 (session) σ 2 = δσ 1 TIES 2002 Genova, June 18-22, 2002 18

Results (cont.) Parameter β σ a σ b σ aa σ bb σ 1 δ lower 0.0157 0.0027 0.0095 0.0026 0.0058 0.0168 0.816 MLE 0.0296 0.0074 0.0170 0.0041 0.0081 0.0177 0.886 upper 0.0436 0.0204 0.0304 0.0066 0.0115 0.0188 0.961 Random effect a 1 * a 2 * b 11 * b 12 * b 13 * b 21 * b 22 * b 23 * lower -0.0126-0.0045-0.0068-0.0137-0.0082-0.0186 0.0072-0.0474 BLUP -0.0101-0.0021 0.0078 0.0009 0.0064-0.0040 0.0218-0.0328 upper -0.0076 0.0003 0.0224 0.0155 0.0209 0.0106 0.0364-0.0182 TIES 2002 Genova, June 18-22, 2002 19

Results (cont.) Bias and accuracy systematic error of -0.01 µt for EMDEX II meters [-0.013 µt, -0.007 µt] relative error of 3% for both instrument types [1.6%, 4.4%] coil 1 coil 2 coil 3 EMDEX II 3.7% [2.9,4.5] 3.1% [2.3,3.8] 3.6% [2.8,4.4] EMDEX Lite 2.6% [1.8,3.6] 5.1% [4.3,5.9] -0.3% [-1.1,0.5] TIES 2002 Genova, June 18-22, 2002 20

0.05 0.04 0.03 0.02 0.01 0 0.01 0.05 0.04 0.03 0.02 0.01 0 0.01 Results (cont.) oriented coil: 1 2 3 EMDEX II EMDEX LITE 0.2 0.4 0.6 0.8 1 0.2 0.4 0.6 0.8 1 reference magnetic flux density EMDEX II EMDEX LITE 0.2 0.4 0.6 0.8 1 0.2 0.4 0.6 0.8 1 3 2 reference magnetic flux density 1 2 1 3 predicted absolute measurement error average absolute measurement error TIES 2002 Genova, June 18-22, 2002 21

Results (cont.) TIES 2002 Genova, June 18-22, 2002 22

Conclusions reliability similar findings in literature for overall bias and relative error [UKCCS (2000)] good agreement with technical specifications by manufacturer [0.01 µt, 1%-2%] agreement EMDEX II possibly biased relative error depends on the level considered needs further investigation! TIES 2002 Genova, June 18-22, 2002 23

Discussion "Perplexities" random effects for instrument type and coil orientation factors model does not obey to weak heredity principle generated magnetic flux density measured without error TIES 2002 Genova, June 18-22, 2002 24

Final remarks extension of one-way random-effects model complex experimental assets parsimony and ease of interpretation epidemiologically relevant influence on the final outcome work in progress TIES 2002 Genova, June 18-22, 2002 25

References Bland, J.M. and Altman, D.G. (1986). Statistical methods for assessing agreement between two methods of clinical measurement. The Lancet i(8476), 307-310. Borsero, M. et al. (2001). Calibration and evaluation of uncertainty in the measurement of environmental electromagnetic fields. Radiation Protection Dosimetry, 97, 363-368. Goldstein, H. (1995). Multilevel Statistical Models. Halstead Press, New York. Lewis, P.A. et al. (1991). The problem of conversion in method comparison studies. Applied Statistics, 40, 105-112. Pinheiro, J.C. and Bates, D.M. (2000). Mixed-Effects Models in S and S- PLUS. Springer-Verlag, New York. SAS Institute Inc. (2001). SAS/STAT Software, Release 8.2. Cary, NC, USA. UKCCS (2000). The United Kingdom Childhood Cancer Study: Objects, materials and methods. British Journal of Cancer, 82, 1073-1102. TIES 2002 Genova, June 18-22, 2002 26