Multilevel modelling and time series analysis in ... - ERSO - Swov

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Chapter 2Results and interpretationThe results now contain two variance-covariance matrices: Ω v and Ω u . Ω vindicates the variance and covariance of intercept and slope across provincesand Ω u across locations. The variance-covariance matrix for the locations is stillrelatively unchanged as compared to the two-level model (2.2.1.4). Forprovinces, the intercept variance is still only marginally significant. The slopevariance and the slope/intercept covariance that have been added to the modelare clearly not significant (to be significant at the .05-level they would have toexceed twice the size of their standard error, which is clearly not the case). Theconclusion that this last extension of the model was not necessary is confirmedby the deviance test. Although the present model estimates two extraparameters, the deviance is exactly the same as that of the simpler model withthe length effect only varying at the level of the locations.To conclude, the speed of cars has shown to vary substantially acrossmeasurement locations and only to a limited extent across provinces. There is arelation between the length of a car and its speed and this relation varies acrossmeasurement locations but not across provinces. The introduction of a thirdlevel has proven of limited use. Not only is the variation attributed to this levelvery limited, but moreover the results for the other levels were almost exactlythe same as in the two-level models.2.2.2.4. ConclusionIt has been shown how to extend the two-level models presented in section2.2.1 to three level models. It has also been demonstrated how to investigate
2.2 Linear multilevel modelswhether the additional level improves the model and in the present case it hasbeen concluded that a two-level model would be sufficient.P r o j e c t c o - f i n a n c e d b y t h e E u r o p e a n C o m m i s s i o n , D i r e c t o r a t e - G e n e r a l T r a n s p o r t a n d E n e r g yP a g e 3 1
Page 1 and 2: Deliverable D7.5Multilevel modellin
Page 3 and 4: 3.6 State space models.............
Page 5 and 6: Chapter 1 - IntroductionHeike Marte
Page 7 and 8: IntroductionFigure 1.2: Structure o
Page 9 and 10: 2.1 Introduction multilevel modelli
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Page 15 and 16: 2.2 Linear multilevel modelsResults
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Page 28 and 29: Chapter 2intercept between location
Page 32 and 33: 2.3 Discrete response models2.3.1 I
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Page 36 and 37: Chapter 2Results and interpretation
Page 38 and 39: Chapter 2Predictor Coefficient π j
Page 40 and 41: 2.3.3 Multinomial responsesHeike Ma
Page 42 and 43: Chapter 2A new response variable ha
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Page 52 and 53: 2.3.4 CountsGeorge Yannis, Eleonora
Page 54 and 55: Chapter 2▪ Click on the N (ΩΧ,
Page 56 and 57: Chapter 2These results are intuitiv
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Page 72 and 73: 2.4 Longitudinal dataHeike Martense
Page 74 and 75: Chapter 2Than open the “Names”
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Page 78 and 79: Chapter 2Results and Interpretation
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Chapter 2Results and Interpretation
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Chapter 2Now a variable that contai
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Chapter 2 Click “Done”• Estim
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Chapter 2As described in the multiv
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Chapter 2▪ Click on resp1 or resp
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Chapter 2Before we proceed in fitti
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Chapter 2▪ Click on the Estimates
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Chapter 2We will now proceed in bui
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Chapter 2A significant regional var
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Chapter 2▪ Click More to run the
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Chapter 2The fixed effect of enforc
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Chapter 3 - Time series analysis3.1
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Chapter 3manual's objective: "even
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Chapter 3The option “Variable Vie
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Chapter 3The figure displayed below
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Chapter 3
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Chapter 3Then mark and click the va
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Chapter 3The residual analysis in t
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Chapter 3A new window “Linear Reg
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Chapter 3The result stated above sh
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Chapter 3The same result is obtaine
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Chapter 3In this new opened window
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Chapter 3To compute the last variab
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Chapter 3
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Chapter 3time series on “Squared
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Chapter 33.2.2 Generalized linear m
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Chapter 3SPSS (Version 14.0) was us
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Chapter 33.4.2 ARIMA models for sta
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Chapter 3• Click on Graphs..Seque
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Chapter 3The ACF plot indicates the
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Chapter 3The ACF plot of the filter
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Chapter 3• Click on Statistics th
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Chapter 3Model Description ARIMA(0,
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Chapter 3In addition to the precedi
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Chapter 3Note that it is very diffi
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Chapter 3In the case the Residuals
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Chapter 3The normal Q-Q plot compar
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Chapter 33.4.4 ARIMA models for sea
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Chapter 33.4.4.2. Model identificat
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Chapter 3The ACF plot indicates obv
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Chapter 33.4.4.3. Model estimation
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Chapter 3• Click on Plots tab and
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Chapter 3Model Description ARIMA (2
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Chapter 33.4.4.4. Graphical results
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Chapter 3Kolmogorov-Smirnov TestIn
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Chapter 3Here are the SPSS results
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Chapter 3of the residuals, up to or
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Chapter 3HistogramQQ-plot
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Chapter 3As the intervention variab
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Chapter 3The addition of the two ex
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Chapter 3Histogram
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Chapter 3Kolmogorov-Smirnov TestIn
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Chapter 33.5 DRAG modelsThe DRAG mo
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Chapter 3a summary of results and s
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Chapter 3This data file consists of
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Chapter 3 Then click on the Finish
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Chapter 3Independence Q(6,6) 28.8 1
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Chapter 3Step 4: Graphics of model
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Chapter 3 Shortly examine the figur
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Chapter 3The STAMP graphics window
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Chapter 334, we better use the Door
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Chapter 3The auxiliary residuals ar
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Chapter 33.6.2.2 Stochastic level m
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Chapter 3convergence criteria used
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Chapter 36.25Log_NO_fatTrend_Log_NO
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Chapter 3 Go to the STAMP window ag
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Chapter 3 Click OK.
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Chapter 3The list of forecast resul
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Chapter 33.6.3 Local linear trend m
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Chapter 3Irr 0.021360 ( 1.0000) Che
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Chapter 3 In the Residual graphics
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Chapter 33.6.3.2. Stochastic linear
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Chapter 3Estimation sample is 1970.
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Chapter 37.0 Log_FI_fat Trend_Log_F
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Chapter 3The goodness-of-fit is cle
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Chapter 3The STAMP graphics window
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Chapter 33.6.4 Local linear trend p
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Chapter 3Prediction error variance
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Chapter 3Parameter estimation sampl
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Chapter 38.007.757.507.257.000.2Log
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Chapter 3Goodness-of-fit results fo
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Chapter 3interpretation of the test
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Chapter 3The text "Lvl 1983.2" appe
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Chapter 3Normality N 2.40 5.99 +Tab
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Chapter 32Residual Log_UKdriversKSI
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Chapter 32IrrRes Log_UKdriversKSI0.
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Chapter 33.6.6 Explanatory variable
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Chapter 3function has increased fro
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Chapter 3Figure 3.6.18: Observed lo
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Chapter 3 Use the menu or to save
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Chapter 32IrrRes Log_UKdriversKSI0.
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Chapter 3for this period. The actua
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Chapter 3the top figure and the ori
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Chapter 4 - ConclusionThe present d
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Chapter 4researchers conduct valid
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ReferencesLISREL for Windows. Scien
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