Lagrange multipliertest, Advanced Statistics

The Null Hypothesis - H0:  There is autocorrelation

The Alternative Hypothesis - H1: There is no autocorrelation

Rejection Criteria: Reject H0 (n-s)R2 >641_Partial Autocorrelation Function1.png = (1515 - 4) x (0.01) = 15.11 > 9.49 (641_Partial Autocorrelation Function1.png)

1515 cases used, 4 cases contain missing values

Since 15.11 > 9.49 the chi-squared value with 4 lags (ET-1, ET-2, ET-3, and ET-4) there is evidence to suggest that we reject H0 meaning that there is no autocorrelation.    

The regression equation is

RESI1 = - 0.0011 + 0.000005 totexp - 0.000001 income + 0.000017 age + 0.00007 nk

        + 0.0085 ET-1 + 0.0070 ET-2 - 0.0284 ET-3 - 0.0074 ET-4

Predictor         Coef     SE Coef                 T      P

Constant       -0.00105     0.01375        -0.08  0.939

totexp          0.00000471  0.00006080   0.08  0.938

income        -0.00000082  0.00004314  -0.02  0.985

age              0.0000167   0.0003090     0.05  0.957

nk                0.000071     0.004785       0.01  0.988

ET-1             0.00847       0.02580         0.33  0.743

ET-2             0.00700       0.02584         0.27  0.786

ET-3           -0.02842       0.02587        -1.10  0.272

ET-4          -0.00743       0.02592         -0.29  0.774

As the T value decreases, the P value increases which is noticeable above due to the inclusions of lags. Most of the T values are now closer to 0 which shows that there is less reliability of the coefficient.  ET-3 will be included in a further regression analysis as it is significant with a value of -1.10, conversely ET-1, ET-2, ET-4 will be removed as they are insignificant with low T values.     

S = 0.0905514   R-Sq = 0.1%   R-Sq(adj) = 0.0%

The inclusion of lags has caused the r-squared to be really low at 0.1% which certainly suggests that the model is inadequate for explaining the Y variable. It also indicates that data points are distributed away from the line of best fit and that the independent variables are poor predictors for the dependent variable. The remaining percentage (99.9%) is the variation which is unknown.

 

Analysis of Variance

 

Source               DF         SS        MS     F      P

Regression        8    0.012127  0.001516  0.18  0.993

Residual Error  1506  12.348529  0.008200

Total                1514  12.360656

Source  DF    Seq SS

totexp   1  0.000029

income  1  0.000005

age       1  0.000011

nk         1  0.000000

ET-1      1  0.000903

ET-2      1  0.000544

ET-3      1  0.009961

ET-4      1  0.000673

Since the F value is small at 0.18 and the P value is high 0.993 it reveals that there is no relationship between the Y dependent variable and X independent variables. This indicates that as it is 0.18 it does not support the model and therefore the slopes are equal to 0.

Posted Date: 3/4/2013 6:39:55 AM | Location : United States







Related Discussions:- Lagrange multipliertest, Assignment Help, Ask Question on Lagrange multipliertest, Get Answer, Expert's Help, Lagrange multipliertest Discussions

Write discussion on Lagrange multipliertest
Your posts are moderated
Related Questions
Incubation period is the time elapsing amongs the receipt of infection and the appearance of the symptoms. The length of the incubation time period depends on the disease, ranging

Observational study   is the study in which the objective is to discover cause-and-effect relationships but in which it is not feasible to use the controlled experimentation, in th

Perturbation theory : The theory useful in assessing how well a specific algorithm or the statistical model performs when the observations suffer less random changes. In very commo

Multilevel models are the regression models for the multilevel or clustered data where units i are nested in the clusters j, for example a cross-sectional study where students are

Persson Rootze ´n estimator  is an estimator for the parameters in the normal distribution when the sample is truncated so that all the observations under some fixed value C are re

Question 1 A box contains 20 fuses of which 5 are defective If 2 fuses are chosen together at random what is the probability that both the fuses are defective? Question 2 A c

when there is tie in sequencing then what we do

Play-the-winner rule is a process sometimes considered in the clinical trials in which the response to treatment is positive (a success) or negative (a failure). One of two treatm

Relative risk is the measure of the association between the exposure to a particular factor and the risk or probability of a convinced outcome, calculated as follows     therefor

A vague concept which occurs all through statistics. Essentially the term means the number of independent units of the information in an easy relevant to the estimation of the para