Type: descriptive statistic   
Computed in Analysis of Covariance (ANCOVA) or in  multiple classification analysis (MCA)
If one correlate is of the nominal level of measurement (subgroups) and (at least0 one other correlate is of the metric level, the happiness means of all the subgroups can be 'adjusted' by shifting the group mean values along the regression line of that subgroup towards the grand average value of the metric correlate, resulting in 'adjusted' means for that subgroup. In that way, effects of differences between mean values of the metric correlate for the different subgroups are eliminated.
Reference: Neter, J. & Wasserman, W. Applied Linear statistical models, R.D. Erwin Inc., Homewood Ill. USA, 1974, p. 712

Type: descriptive statistic   
Computed in Analysis of Covariance (ANCOVA) or in  multiple classification analysis (MCA)
If one correlate is of the nominal level of measurement (subgroups) and (at least0 one other correlate is of the metric level, the happiness means of all the subgroups can be 'adjusted' by shifting the group mean values along the regression line of that subgroup towards the grand average value of the metric correlate, resulting in 'adjusted' means for that subgroup. In that way, effects of differences between mean values of the metric correlate for the different subgroups are eliminated.
Reference: Neter, J. & Wasserman, W. Applied Linear statistical models, R.D. Erwin Inc., Homewood Ill. USA, 1974, p. 712

Type: descriptive statistic   
Computed in Analysis of Covariance (ANCOVA) or in  multiple classification analysis (MCA)
If one correlate is of the nominal level of measurement (subgroups) and (at least0 one other correlate is of the metric level, the happiness means of all the subgroups can be 'adjusted' by shifting the group mean values along the regression line of that subgroup towards the grand average value of the metric correlate, resulting in 'adjusted' means for that subgroup. In that way, effects of differences between mean values of the metric correlate for the different subgroups are eliminated.
Reference: Neter, J. & Wasserman, W. Applied Linear statistical models, R.D. Erwin Inc., Homewood Ill. USA, 1974, p. 712

Type: descriptive statistic   
Computed in Analysis of Covariance (ANCOVA) or in  multiple classification analysis (MCA)
If one correlate is of the nominal level of measurement (subgroups) and (at least0 one other correlate is of the metric level, the happiness means of all the subgroups can be 'adjusted' by shifting the group mean values along the regression line of that subgroup towards the grand average value of the metric correlate, resulting in 'adjusted' means for that subgroup. In that way, effects of differences between mean values of the metric correlate for the different subgroups are eliminated.
Reference: Neter, J. & Wasserman, W. Applied Linear statistical models, R.D. Erwin Inc., Homewood Ill. USA, 1974, p. 712

Type: descriptive statistic   
Computed in Analysis of Covariance (ANCOVA) or in  multiple classification analysis (MCA)
If one correlate is of the nominal level of measurement (subgroups) and (at least0 one other correlate is of the metric level, the happiness means of all the subgroups can be 'adjusted' by shifting the group mean values along the regression line of that subgroup towards the grand average value of the metric correlate, resulting in 'adjusted' means for that subgroup. In that way, effects of differences between mean values of the metric correlate for the different subgroups are eliminated.
Reference: Neter, J. & Wasserman, W. Applied Linear statistical models, R.D. Erwin Inc., Homewood Ill. USA, 1974, p. 712

Type: descriptive statistic   
Computed in Analysis of Covariance (ANCOVA) or in  multiple classification analysis (MCA)
If one correlate is of the nominal level of measurement (subgroups) and (at least0 one other correlate is of the metric level, the happiness means of all the subgroups can be 'adjusted' by shifting the group mean values along the regression line of that subgroup towards the grand average value of the metric correlate, resulting in 'adjusted' means for that subgroup. In that way, effects of differences between mean values of the metric correlate for the different subgroups are eliminated.
Reference: Neter, J. & Wasserman, W. Applied Linear statistical models, R.D. Erwin Inc., Homewood Ill. USA, 1974, p. 712

Type: descriptive statistic   
Computed in Analysis of Covariance (ANCOVA) or in  multiple classification analysis (MCA)
If one correlate is of the nominal level of measurement (subgroups) and (at least0 one other correlate is of the metric level, the happiness means of all the subgroups can be 'adjusted' by shifting the group mean values along the regression line of that subgroup towards the grand average value of the metric correlate, resulting in 'adjusted' means for that subgroup. In that way, effects of differences between mean values of the metric correlate for the different subgroups are eliminated.
Reference: Neter, J. & Wasserman, W. Applied Linear statistical models, R.D. Erwin Inc., Homewood Ill. USA, 1974, p. 712

Type: descriptive statistic   
Computed in Analysis of Covariance (ANCOVA) or in  multiple classification analysis (MCA)
If one correlate is of the nominal level of measurement (subgroups) and (at least0 one other correlate is of the metric level, the happiness means of all the subgroups can be 'adjusted' by shifting the group mean values along the regression line of that subgroup towards the grand average value of the metric correlate, resulting in 'adjusted' means for that subgroup. In that way, effects of differences between mean values of the metric correlate for the different subgroups are eliminated.
Reference: Neter, J. & Wasserman, W. Applied Linear statistical models, R.D. Erwin Inc., Homewood Ill. USA, 1974, p. 712

Type: descriptive statistic   
Computed in Analysis of Covariance (ANCOVA) or in  multiple classification analysis (MCA)
If one correlate is of the nominal level of measurement (subgroups) and (at least0 one other correlate is of the metric level, the happiness means of all the subgroups can be 'adjusted' by shifting the group mean values along the regression line of that subgroup towards the grand average value of the metric correlate, resulting in 'adjusted' means for that subgroup. In that way, effects of differences between mean values of the metric correlate for the different subgroups are eliminated.
Reference: Neter, J. & Wasserman, W. Applied Linear statistical models, R.D. Erwin Inc., Homewood Ill. USA, 1974, p. 712

Type: descriptive statistic   
Computed in Analysis of Covariance (ANCOVA) or in  multiple classification analysis (MCA)
If one correlate is of the nominal level of measurement (subgroups) and (at least0 one other correlate is of the metric level, the happiness means of all the subgroups can be 'adjusted' by shifting the group mean values along the regression line of that subgroup towards the grand average value of the metric correlate, resulting in 'adjusted' means for that subgroup. In that way, effects of differences between mean values of the metric correlate for the different subgroups are eliminated.
Reference: Neter, J. & Wasserman, W. Applied Linear statistical models, R.D. Erwin Inc., Homewood Ill. USA, 1974, p. 712

Type: descriptive statistic   
Computed in Analysis of Covariance (ANCOVA) or in  multiple classification analysis (MCA)
If one correlate is of the nominal level of measurement (subgroups) and (at least0 one other correlate is of the metric level, the happiness means of all the subgroups can be 'adjusted' by shifting the group mean values along the regression line of that subgroup towards the grand average value of the metric correlate, resulting in 'adjusted' means for that subgroup. In that way, effects of differences between mean values of the metric correlate for the different subgroups are eliminated.
Reference: Neter, J. & Wasserman, W. Applied Linear statistical models, R.D. Erwin Inc., Homewood Ill. USA, 1974, p. 712

Type: descriptive statistic   
Computed in Analysis of Covariance (ANCOVA) or in  multiple classification analysis (MCA)
If one correlate is of the nominal level of measurement (subgroups) and (at least0 one other correlate is of the metric level, the happiness means of all the subgroups can be 'adjusted' by shifting the group mean values along the regression line of that subgroup towards the grand average value of the metric correlate, resulting in 'adjusted' means for that subgroup. In that way, effects of differences between mean values of the metric correlate for the different subgroups are eliminated.
Reference: Neter, J. & Wasserman, W. Applied Linear statistical models, R.D. Erwin Inc., Homewood Ill. USA, 1974, p. 712