+ Under the Taylor-Russell
model, you specify the percentage of employees considered successful prior to
introducing a new selection tool, the selection ratio you plan to use, and the
correlation between the selection tool and job performance. The program
calculates the percentage of selected employees expected to be successful.
+ With the Lawshe
et al. model, you decide what predictor score intervals you want information
about, the percentage of employees considered successful prior to introducing a
new selection tool, and the correlation between the selection tool and job
performance. The program calculates the percentage of applicants within each
score interval that would be expected to succeed on the job if hired.
+ Under the Naylor-Shine
model, you provide the mean and standard deviation of job performance of
employees that is obtained without the selection tool, the selection ratio you
plan to use, and the correlation between the selection tool and job performance.
The program calculates the expected mean performance level of the group that is
hired using the specified selection ratio.
Assumptions For More Information
Taylor, H. C. & Russell, J. T. (1939). The relationship of validity
coefficients to the practical effectiveness of tests in selection: Discussion
and tables. Journal of Applied Psychology, 23, 565-578.
The question addressed by this model is, what proportion of the selected
group can be expected to perform at or above the level that minimally defines
success, given a specific selection ratio and correlation coefficient?
The reference for the Lawshe et al. model is:
Lawshe, C. H., Bolda, R. A., Brune, R. L., & Auclair, G. (1958).
Expectancy charts II: Their theoretical development. Personnel Psychology, 11,
545-559.
The question addressed by this model is, what proportion of the group whose
predictor scores fall between two points is expected to be successful, given a
particular correlation coefficient and a specified prior rate of success?
The reference for the Naylor-Shine model is:
Naylor, J. C. & Shine, L. C. (1965). A table for determining the increase
in mean criterion score obtained by using a selection device. Journal of
Industrial Psychology, 3, 33-42.
The question addressed by this model is, what is the expected mean job
performance level of a group of applicants with predictor scores at or above a
particular minimum, given the mean and standard deviation of job performance
without the predictor, and a particular correlation coefficient?
There are four main screens you will use in this program - a "home window"
and one window for each of the three expectancy models. You start out in the
home window, where you choose the model that you want to use, and enter
descriptive information about the predictor (i.e., the selection procedure).
Then, clicking on the "Continue" button brings up the window for the model
you have chosen.
Starting out
The basic concept in this program is that on each window, there is an area
for user input, and an area for results. Each item is clearly labeled, and once
all required input has been entered, clicking the "Calculate" button initiates
the computation of results.
Any piece of information that you will need to type in is shown as a box like
this one:
On all windows, the specific characters that you can type into the yellow
entry fields are only those that would lead to valid values. For example, you
will not be allowed to enter a negative sign in a field that is asking for a
percentage between zero and 100. Text can be pasted into these fields from the
Windows clipboard too, although characters that are not appropriate for the
field will not be flagged until calculations are attempted.
Entry of characters is limited to the width of the entry field itself. Once
the maximum allowed number of characters has been reached, no more input will be
accepted. This is to ensure that no characters will scroll out of view, so that
all results and input data are correctly displayed at all times (especially
important if you are retaining printouts). You can, of course, use the direction
keys, the backspace key, and the delete key to edit the entry you are making.
Finally, you will notice that when you change values in many of the entry
fields after computing results, any results that depend on the value you changed
will be erased. This includes any changes to the predictor mean and standard
deviation on the home window. If these values are changed, dependent results on
other windows will be erased when you switch back to those windows. Again, this
is to avoid any possibility of displaying results based on values that are no
longer showing in the input fields of the window.
Overview 1 - Expectancy Models
Models
This program is used to estimate the amount of workforce
improvement that can be realized by implementing a valid selection procedure in
an organization. The program quickly and accurately computes institutional
expectancies under three different models, based on information that you supply:
All of these models assume a bivariate normal
relationship between applicant scores on the selection tool and job performance.
In practice, this assumption is often satisfied reasonably well when
professional standards are observed in the development of predictors and the
measurement of job performance. Users should be familiar with the implications
of this assumption when interpreting the results calculated by the program.
For more discussion of these expectancy models
and their underlying computations, see Theoretical expectancies: Replacing
classic tables with flexible, accurate computing procedures by Richard A.
McLellan, a paper presented at the 12th Annual Conference of the Society for
Industrial and Organizational Psychology, April 1997.
Taylor-Russell Model
The reference for the Taylor-Russell model is:
Lawshe et al. Model
Naylor-Shine Model
Overview 2 - Program Layout
Navigating Between Windows
When you first start the Theoretical Expectancy
Calculator and clear the welcome screen, you will be in the home window. To get
past this window, you must first select one of the three expectancy models and
type in the mean and standard deviation of the predictor in the yellow entry
fields (see Entering Required Input). After that, simply click on the "Continue"
button and a window will open for the expectancy model you have selected.
Entering Required Input