Open Access e-Journal Cardiometry No.16 May 2020

The statistical analysis of the obtained data has
been performed using statistical package STADIA 8.0.
Results and discussion
The obtained statistical patterns in determining
the SI values for various emotional states in the respondents
are presented in Table 1 herein.
The first column in the present and all the following
tables shows the numbers to indicate the following
emotional states, which appear, when the respondents
have fixed their attention:
1) on those metaphoric cards, which are associated
with their highest unreadiness/worst conditioning for
an important exam;
2) on those metaphoric cards, which are associated
with their highest readiness/best conditioning for an
important exam;
3) on those metaphoric cards, which are associated
with their highest unreadiness/ worst conditioning for
an important examination period;
4) on metaphoric cards, which are associated with
their highest readiness/ best conditioning for an important
examination period;
5) on metaphoric cards, which are associated with
their highest unreadiness/ worst conditioning for any
important life’s trial;
6) on metaphoric cards, which are associated with
their highest readiness/ best conditioning for any important
life’s trial;
7) on all simultaneously considered metaphoric cards,
which are associated with their highest readiness/ best
conditioning for an important exam, an examination
period, any life’s trial;
8) on the freely swinging pendulum on a tripod and
on how the pointed part of the pendulum weight
draws elliptical trace designs in sand at the pendulum’s
bottom.
The static significance of differences in mean values
was confirmed using the χ criterion (chi-square),
which, as noted above, has been assessed using statistical
package STADIA 8.0.
To identify a latent structure of the obtained data
collection, a factor analysis has been conducted. Besides,
it has been also taken into account that the distribution
of the calculated indicators of the heart rate
variability SI values differ from the Gauss-Laplace distribution.
Therefore, in order to identify the correlation
relationships, we have used the Spearman rank
correlation and the Kendall concordance coefficients.
Since the nature of the identified relationships for each
of these coefficients is similar, the data for the Spearman
coefficient are given by us herein only because of
greater generality of the latter.
The factor analysis has been performed by calculating
the correlation matrix of the major components
with their further rotation to obtain the simplest interpretable
factor system, based on the STADIA 8.0
statistical package developer’s recommendations [4].
At the same time, the major axes of the ellipse of analyzed
objects’ scattering, eigenvalues of which are
greater than 1, have been taken into consideration as
the main components. For the purpose of an interpretable
description of the factors, marker variables have
been utilized, which provide for a meaningful interpretation
of their possible nature. In doing so, the variables
with a high interrelationship with a given factor
exactly have been chosen as the above variables
In our explorative factor analysis, conducted has
been a step-by-step reduction of the number of the
main components, followed by Varimax rotation for
formulating a hypotheses on the optimal factor structure
of the studied latent relations. The obtained data
allowed suggesting that, as shown in Table 2 herein,
the optimal structure should include 4 factors.
During the confirmatory factor analysis, in order
to verify the hypothesis for the optimal factor structure
in the studied latent relations, a more detailed
calculation of factor loadings, reflecting their geomet-
Table 1
The main statistical parameters of the SI values for various emotional states in the respondents
Ego-states Arithmetic mean Standard deviation Median Asymmetry Excess
1 429 378,6 290 2,019 8,042
2 292,1 209,8 231 1,286 4,589
3 343,9 276,2 262 1,874 7,926
4 298,7 250,8 223 2,163 8,904
5 330,7 260,1 290 3,141 19,3
6 273,7 234,4 199 2,21 9,143
7 242,1 166,4 204 1,419 5,453
8 276,7 198,7 256 1,319 4,555
Issue 16. May 2020 | Cardiometry | 57