Summary of Employee Performance
The scores of the variable employee performance were computed to come up with a simple average
of the scores in each component. Table 4.28 presents a summary of Employee performance as
shown in the study. The results are given below the table.
Means and Standard
Performance
N
Mean Std. Deviation
Task performance
Contextual performance
a) Teamwork
b) Effort
c) Personal discipline
Average performance rating on contextual
performance
288
288
4.176
4.398
4.295
4.251
4.279
0.940
0.759
0.883
0.840
0.855
288
288
288
Cronbach alpha coefficient = 0.85
Deviations for Measures of performance
,,
This analysis shows that the level of performance in Kenyan state corporations was rated as high
by respondents (mean 4.279 and SD 0.855). The respondents by consensus rated the level of Task
performance as high, shown by the standard deviation recording less than 1. On contextual
performance the respondents level of Teamwork scored the highest (Mean 4.398, SD 0.759)
followed by the level of effort (Mean 4.295, SD 0.883), level of personal discipline (Mean 4.251,
SD 0.840). In these four sub variables, respondents agreed by consensus in rating employee
performance in their organization as high. The analysis implies that respondents by consensus
rated the level of employee performance in their organization as high as shown by the mean and
standard deviation in the four sub variables. This was indicated by the standard deviations in all
responses being below 1. Generally, the level of employee performance in Kenyan state
corporations is high. This may be explained by the fact that different State Corporations provide
different levels of training, HRM practices, incentives and hire different quality of staff in various
departments as there are no fixed guidelines and standards to control the training type, incentives
and conditions for hiring in state corporations.
Diagnostic tests
The use of parametric statistics such as multiple regression and correlation requires that the
sample data is normally distributed and has homogeneity of variance. Since multiple regression
and correlation was to test the formulated hypotheses in this study, preliminary tests of normality,
linearity and multi collinearity were administered to get rid of any violation of normality,
linearity, multi collinearity and that data was normally distributed and had homogeneity of
variance. Meaning that the deviation from the mean of these variables was uniformly spread. The
deviation ranged between .2 and -.195.
Tests of Normality
Preliminary analysis to assess and test if the data fits a normal distribution was conducted.
Normality is central to statistics and was assessed by obtaining the skewness and kurtosis values
of the distributed scores. Skewness indicates symmetry of the distribution while kurtosis indicates
the “peakedness” of the distribution. A value of zero indicates a perfectly normal distribution.
As seen in Table 4.30 below, Employee performance, Employee age, Human Resource
Management Practices and Employee Competence data were normally distributed as shown by
homogeneity of variance since the data did not indicate extreme departures from the Mean, which
are the normality assumptions
Results of Tests of normality
Scale Skewness Kurtosis
1 Employee Performance .289 1.006
2 Employee Age -.195 .172
3 Human Resource Management Practices .208 .219
4 Employee Competence .214 -.230
Tests of Linearity
Linearity was tested by use of scatter plots which are normally used to assess the relationship between
two continuous variables and testing whether the variables are related in a linear (straight line) or
curvilinear fashion before carrying out correlation analysis. The scatter plots are shown on appendix
IX. The relationship between the variables should be fairly linear. The test showed a moderate and
positive relationship between HRM Practices and employee performance, but a weak positive
relationship between employee age and employee performance. The relationship between HRM
Practices and employee age is positive but weak. The relationship between employee competence and
employee performance was positive and moderate. The relationship between employee age and
employee competence was weak. This analysis showed that linearity existed between the variables of
the study.
,
Relationship among the Study Variables
The linkages and relationships among the various study variables as shown in the conceptual
framework provided the foundation for this study. These variables include Employee age (young
employees, middle age employees and older employees), Human resource management practices
(employee participation and empowerment, compensation benefits, employee training and
development, employee welfare benefits and performance management), Employee competence
(educational level, skills level, training level and experience) and employee performance (Task
performance and contextual performance). Correlation analysis was conducted to investigate the
relationships between the study variables. This investigation was aimed at establishing if a
relationship exists between the study variables, the direction and strength of the relationship, before
carrying out further analysis, in particular, regression analysis to determine the extent, and effect of
the magnitude of the relationship. The correlation coefficients give preliminary indications of what
to expect in subsequent inferential statistical analyses.
The investigation also aimed at determining the existence and nature of relationships among the
indicators of dependent and independent variables. Keller and Warrack, (2000), Green et al.
(1988) and Lehman et al. (1998) consider Correlation of 0.9 and 0.7 respectively as a threshold of
correlations used in analyzing the effect of collinearity on the study variables. Data was collected
using the Interval Likert - type scale and Pearson’s product moment correlation technique was
used to determine the strength and direction of the relationship between the study variables. Table
4.30 presents the results of the correlation between the study variables.
Correlation among Variables
Data used to asses hypotheses were obtained by asking respondents to rate the items on the
questionnaires on employee age, HRM practices, employee competence and employee
performance. To find the relationship between these study variables, ie employee age, Human
Resource management practices, employee competence and employee performance, correlation
was conducted through Pearson's Product Moment Correlation technique.
Table 4.31 presents the results of the correlation analysis between employee performance and
employee age, HRM practices and employee competence. The purpose of this correlation was to
test for the magnitude, strength and direction of the relationship among the dependent,
independent, and moderating variables of the study to compare the contribution of each variable
in this relationship.
Results of the test for the relationship between employee age, HRM practices,
employee competence and employee performance.
EMPLOYEE
PERFORMANCE
EMPLOYEE
AGE
HRM PRACTICES EMPLOYEE
COMPETENCE
EMMPLOYEE
PERFORMANCE
1 -.002* * .105* * .211* *
EMPLOYEE AGE 1 -.052*-.001* *
HRM PRACTICES 1 .302* *
EMPLOYEE
COMPETENCE
1
,**
Correlation
i
s
signi
f
ican
t
a
t
the
0.01
le
v
el
(
2-tailed). p = ˂ 0.01 (2- tailed)
* Correlation is significant at the 0.05 level (1-tailed). p = ˂0.05 (2- tailed)
