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, 1994a; Sidot, 1994; Wallin, 1994) Large, possibly irreconcilable, variations are evident in the models and methods of training and in the amount of experience deemed necessary for nationally accredited recognition as professional psychologists across different countries One country (Austria) has a law specifying the tasks to be performed by professional health psychologists In the remainder, the tasks and responsibilities of professional health psychologists (and, for most countries, other applied psychologists as well) are dependent on a complex array of national, regional, and local agreements Training practices are equally diverse In a few countries, training programs are well advanced and have been implemented by national associations (eg, Berufsverband Osterreichischer Psychologen, 1995; Dansk Psykologforening, 1996) Other associations are making progress in formulating and implementing training guidelines (eg, British Psychological Society: Edelmann et al, 1996; Rumsey et al, 1994b; Berufsverband Deutscher Psychologen: Rielander, 1995).

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However, many European countries still do not yet train health psychologists in any speci c and specialized manner If health psychology is to achieve its full potential in European health care systems, training will need to be implemented much more widely than is presently the case This will only be possible within the particular legal and professional conditions that determine the organization of psychology and health care in different countries A principle of subsidiarity must therefore operate However, it will be necessary to at least have a framework for training in each country and these guidelines provide that framework..

Here it is clear that what is being modeled is the probability that Y = 1. Now Equation 20.1 becomes Y = + . Consider the error term. Because Y is binary, the error takes on only two values: 1 when Y is 1, and when Y is 0. The ordinary least squares (OLS) estimators of the s are still unbiased because the mean of the errors is still zero. To see this, note that the mean of the errors is E( ) = p( ) = (1 ) + ( ) (1 ) = 0. But the variance of the errors is no longer constant over levels of X. This is evident in the expression for the error variance: 2 ( E( )) 2 p( ) = p( ) = (1 ) 2 + V( ) = 2 ( ) (1 ) = (1 )[(1 ) + ] = (1 ). Because Equation 20.3 shows to be a function of the Xs, the error variance is, too. Thus, the LPM is inherently heteroscedastic. This condition has two consequences. First, the OLS estimators are no longer ef cient there exist other estimators with smaller sampling variance. More important, OLS estimates of the standard errors of the coef cients are

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Figure 11-1

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Summary

of the wall, or the distance from the wall base that the ant started its journey, was altered In either case the effect would be a mismatch between the correct 45 elevation and the actual elevation of the top of the wall So for example some ants were placed 20 centimeters from a 40-centimeter-high wall In this scenario the elevation of the top of the wall is of course too high, and as would be predicted the ants were observed to move gradually away from the wall as they walked, thereby lowering the elevation Similarly ants placed 40 centimeters away from a 20-centimeterhigh wall (elevation too low) moved towards the wall as they walked So it would appear that in both cases the ants could use the mismatch between the elevation that they had learned and the one that they observed to correct their course.