Development of superior chitosan–EDTA microparticles as an adsorbent base for solidifying the self-emulsifying drug delivery systems

Future Journal of Pharmaceutical Sciences

Table 3 Least squares fit effect summary

Response	R²	R² Adj	RMSE	MR	Observation
Summary of fit (SE-CHEM)
Y	0.956	0.9298	1.443	89.188	9
ZP	0.825	0.7207	1.568	3.553	9
PS	0.939	0.9025	2.415	11.735	9
Summary of fit (SD-CHEM)
Y	0.992	0.981	1.704	37.07	6
ZP	0.913	0.783	1.476	0.62	6
PS	0.956	0.892	0.348	3.85	6

Response	Source	DF	SS	MS	F Ratio
Analysis of variance (SE-CHEM)
Y	Model	3	227.42	75.81	36.36
	Error	5	10.42	2.08	Prob > F
	C. Total	8	237.84		0.0008*
ZP	Model	3	58.15	19.38	7.88
	Error	5	12.29	2.45	Prob > F
	C. Total	8	70.45		0.0243*
PS	Model	3	450.02	150.009	25.7
	Error	5	29.18	5.837	Prob > F
	C. Total	8	479.21		0.0018*
Analysis of variance (SD-CHEM)
Y	Model	3	760.41	253.46	87.22
	Error	2	5.81	2.91	Prob > F
	C. Total	5	766.21		0.0114*
ZP	Model	3	46.01	15.33	7.03
	Error	2	4.35	2.17	Prob > F
	C. Total	5	50.36		0.127
PS	Model	3	5.38	1.79	14.79
	Error	2	0.24	0.12	Prob > F
	C. Total	5	5.62		0.064

Response	Term	Estimate	SE	t Ratio	Prob >\|t\|
Parameter estimates (SE-CHEM)
Y	Intercept	89.18	0.48	185.32	< 0.0001*
	CH(1,3)	5.71	0.58	9.7	0.0002*
	DT(1,3)	1.91	0.58	3.25	0.0227*
	CH × DT	− 1.52	0.72	− 2.11	0.0883
ZP	Intercept	3.55	0.52	6.8	0.0010*
	CH(1,3)	3.11	0.64	4.85	0.0047*
	DT(1,3)	0.19	0.64	0.3	0.7758
	CH × DT	− 0.06	0.78	− 0.09	0.9335
PS	Intercept	11.73	0.8	14.57	< 0.0001*
	CH(1,3)	− 7.62	0.98	− 7.73	0.0006*
	DT(1,3)	− 3.18	0.98	− 3.23	0.0233*
	CH × DT	3.17	1.2	2.63	0.0466*
Parameter estimates (SD-CHEM)
Y	Intercept	37.07	0.69	53.27	0.0004*
	CH	5.51	0.69	7.91	0.0156*
	DT(1,3)	− 5.36	0.85	− 6.29	0.0243*
	CH × DT	− 10.76	0.85	− 12.63	0.0062*
ZP	Intercept	0.62	0.61	1.03	0.4118
	CH	2.12	0.61	3.53	0.0718
	DT(1,3)	0.75	0.73	1.02	0.4152
	CH × DT	− 2.03	0.73	− 2.76	0.11
PS	Intercept	3.85	0.14	27.13	0.0014*
	CH	− 0.86	0.14	− 6.07	0.0261*
	DT(1,3)	− 0.23	0.17	− 1.35	0.3099
	CH × DT	0.41	0.17	2.4	0.1382

* It indicates that the p value is significant. The model is significant
DF-Degree of freedom, MR-mean of response, MS-mean of squares, PS-particle size, RMSE-root mean square error, SS-sum of squares, Y-percentage yield, ZP-zeta potential