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Week
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Topics
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Study Metarials
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1
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The basic assumptions in the regression models
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R1, P2
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2
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The problem of serial correlation and its effect in the regression models
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R2, P2
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3
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The methods presented as a solution to serial correlation
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R3, P3
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4
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The mixed-effect modeling as a solution to the serial correlation
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R2, P3
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5
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Linear and Nonlinear mixed-effect modeling
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R3, P2
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6
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The determination of fixed effect- and random effect-parameters in mixed effect modeling
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R4, P2
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7
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The comparisons of the technique used for fitting the mixed effect modeling
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R3, P4
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8
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The BLUP techniques for the prediction of random-effect parameters in the mixed effect modeling
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R4, P5
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9
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The determination of calibration response in mixed effect modeling
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R3, P4
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10
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The information criteria for used in the comparing of mixed effect modeling
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R4, P5
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11
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The comparing of statistical software used for fitting the mixed-effect modeling
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R4, P3
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12
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The fitting of mixed effect modeling by a statistical package and writing source code-I
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R5, P4
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13
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The fitting of mixed effect modeling by a statistical package and writing source code-II
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R4, P5
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14
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The sample application of mixed effect modeling with actual data
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R5, P6
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