Statistical Analysis
Data analysis was performed by SPSS® Statistics
software V. 21 (IBM®, Chicago, USA).
Mean and standard deviations were calculated for continuous variables
(i.e. age, age at onset, duration of illness etc.) and percentages
calculated for categorical values. Chi-square test for variance
(χ2) was applied to categorical socio-demographic
data, assumed to be normally distributed (i.e. gender/ age differences).
Student’s t-test was used to
analyze statistical
significance of differences between the
means of continuous
variables (i.e. age/gender vs. medication usage, predictability of
attacks etc.). Analysis of variance (ANOVA) and multivariate analysis of
variance (MANOVA, unidirectional with repeated measurements) were used
to assess differences between prodromes and attacks, as related to
personal categorical values. Pearsons’ correlation coefficient was
calculated for associations between continuous personal variables and
scalable parameters. Stepwise Hierarchical Regression analysis was used
to assess the contribution of health-related personal variables of
prodromes to variables of attack, in which the personal health variables
were forcedly introduced first, prodrome variables second, and thirdly-
the interactions between personal and prodrome variables. Sensitivity
and specificity computations assessed the clinical utility of the new
instruments.