Table 6.

Results of logistic regression analysis and odds ratio of logistic regression model in the group of caregivers. Explained variable: Unmet needs (0—more unmet needs, 1—fewer unmet needs) in caregivers.

Explanatory Variables		bi	SEi	zi	pi = Pr (> |zi|)
Models with two explanatory variables
Model 1 (n = 161)
Chi2 = 9.66, df = 2, p = 0.008, pseudo R2 =0.04
	Intercept	–	–	–	–
X1	Gender	0.919	0.320	2.874	0.004
X2	Age	−0.023	0.008	−2.980	0.003
Model 2 (n = 161)
Chi2 = 4.97, df = 2, p = 0.083, pseudo R2 = 0.02
	Intercept	–	–	–	–
X1	Gender	0.506	0.242	2.085	0.037
X3	Marital status	−0.335	0.157	−2.134	0.033
Models with three explanatory variables
Model 3 (n = 161)
Chi2 = 11.15, df = 3, p = 0.011, pseudo R2 = 0.05
	Intercept	–	–	–	–
X4	Place of residence	0.340	0.115	2.955	0.003
X5	Education	−0.117	0.059	−1.978	0.048
X8	Employment	−0.161	0.063	−2.559	0.011
OR		Per Unit			Per Range
		OR	95% CI	1/OR	OR	95% CI	1/OR	range
From Model 1
X1	Gender (1–2)	2.51	1.36–4.81	1.77	2.51	1.36–4.81	0.40	1
X2	Age (17–95)	0.98	0.96–0.99	0.99	0.16	0.05–0.52	6.07	78
From Model 2
X3	Marital status (1–4)	0.72	0.52–0.98	1.40	0.37	0.14–0.90	2.73	3
From Model 3
X4	Place of residence (1–4)	1.40	0.52–1.77	0.71	2.77	1.43–5.56	0.36	3
X5	Education (1–7)	0.89	0.52–0.99	1.12	0.50	0.24–0.98	2.02	6
X8	Employment (1–6)	0.85	0.52–0.96	1.17	0.45	0.24–0.82	2.24	5

Legend: OR—odds ratio; CI—95% confidence interval for OR. Chi-squared—statistical hypothesis test of Chi² model adjustment; df—number of degrees of freedom; p—calculated level of test significance; pseudo R²—value which evaluates explanatory variable anticipation according to the model; b_i—coefficient estimation in regression model; SE_i—standard error estimation for b_i coefficient; z_i—value of test statistics in standard distribution; (p_i = Pr (> |z_i|)—calculated probability value p_i for double-sided critical area equal to z; n-group quantity.