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Genetic Growth Curve Models: Practical Approach

This paper discusses genetic growth curve models and their practical implementation. It includes matrices, phenotypic growth curve models, twin correlations, and model fitting results.

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Genetic Growth Curve Models: Practical Approach

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  1. Genetic Growth Curve Models Practica Boulder, March 2008 Irene Rebollo & Gitta Lubke & Mike Neale VU Amsterdam NL & Notre Dame, US & VCU, US

  2. 1 0.5/1 1 0.5/1 1 1 1 1 1 1 1 1 1 1 1 1 Es Cs As Ei Ci Ai Ai Ci Ei As Cs Es es cs as eis as cs es eis cis cis ei ci ai ai ci ei ais ais s s i i Agg911 Agg951 Agg971 Agg001 Agg912 Agg952 Agg972 Agg002 Genetic Growth Curve Model

  3. ris Vs Vi s i αs αi 1 1 1 1 0 2 3 4.5 0 0 0 0 1. Phenotypic Growth Curve Model Agg912 Agg952 Agg972 Agg002 e1 e2 e3 e4

  4. ris Vs Vi s i αs αi 1 1 1 1 0 2 3 4.5 0 0 0 0 Agg912 Agg952 Agg972 Agg002 e1 e4 e2 e3 1. Phenotypic Growth Curve Model: Matrices phenLingrow_lib08.mx RUN

  5. ris Vs Vi s i αs αi 1 1 1 1 0 2 3 4.5 0 0 0 0 Agg912 Agg952 Agg972 Agg002 e1 e4 e2 e3 1. Phenotypic Growth Curve Model: Matrices COVARIANCES MEANS

  6. -1.18 0.4 12.3 s i -.38 10.03 1 1 1 1 0 2 3 4.5 Agg912 Agg952 Agg972 Agg002 9.9 7.4 5.4 5.8 1. Phenotypic Growth Curve Model: Run! phenLingrow_lib08.mx FIT: Δχ2 (5)= 28.78, p<.01 RMSEA = .0364 • POSSIBLE SUBMODELS: • Sig. Variation on Slope? • Sig i-s covariance? • Age effect = across surveys? • Significant change across time (αs)? •  All significant!

  7. s i ris ris Vs Vi Vi Vs i s Agg911 Agg951 Agg971 Agg001 Agg912 Agg952 Agg972 Agg002 2. Twin Correlations on the Growth Curve Model (Co)Variance matrix between Intercept & Slope: 1. Phenotypic, within twin co(variances)

  8. s i ris ris Vs Vi Vi Vs i s Agg911 Agg951 Agg971 Agg001 Agg912 Agg952 Agg972 Agg002 2. Twin Correlations on the Growth Curve Model MZ DZ (Co)Variance matrix between Intercept & Slope: 2. Cross twin-within trait: i1-i2 & s1-s2

  9. s i ris ris Vs Vi Vi Vs i s Agg911 Agg951 Agg971 Agg001 Agg912 Agg952 Agg972 Agg002 2. Twin Correlations on the Growth Curve Model MZ DZ (Co)Variance matrix between Intercept & Slope: 3. Cross twin-cross trait: i1-s2 & s1-i2

  10. s i Agg911 Agg951 Agg971 Agg001 2. Twin Correlations on the Growth Curve Model Vs Vi Vi Vs i s Agg912 Agg952 Agg972 Agg002 TWLingrow_lib08.mx RUN

  11. MZ Sym DZ Sym 2. Twin Correlations: Matrices (for covariance structure) COMMON MATRICES ZYGOSITY SPECIFIC COVARIANCE (I@F)&M + (I@R) ; Residuals Tw1 Residuals Tw2 Uncorrelated Residuals COVARIANCE (I@F)&S + (I@R) ;

  12. MZ Sym Sym Sym DZ Sym 2. Twin Correlations: Script & Output CORRELATIONS FOR MODEL SELECTION

  13. MZ Sym Sym Sym DZ Sym 2. Twin Correlations: Script & Output COVARIANCES FOR STARTING VALUES

  14. 1 0.5/1 1 0.5/1 1 1 1 1 1 1 1 1 1 1 1 1 Es Cs As Ei Ci Ai Ai Ci Ei As Cs Es es cs as eis as cs es eis cis cis ei ci ai ai ci ei ais ais s s i i Agg911 Agg951 Agg971 Agg001 Agg912 Agg952 Agg972 Agg002 3. Genetic Growth Curve Model

  15. 3. Genetic Growth Curve Model Lingrow_lib08.mx RUN

  16. 3. Genetic Growth Curve Model: Matrices MZ DZ M = A+C+E | A+C _ A+C | A+C+E; S = A+C+E | H@A+C _ H@A+C | A+C+E; COVARIANCE (I@F)&M + (I@R) ; COVARIANCE (I@F)&S + (I@R) ;

  17. 3. Genetic Growth Curve Model: Script & Output In Matrix K: • Exercise: • Use the option Multiple to Test for genetic effects on: • Covariance i-s • Variance I • Variance S

  18. 3. Genetic Growth Curve Model: Model Fitting Results

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