Strategies to estimate the characteristics of 24-hour IOP curves of treated glaucoma patients during office hours

BMC Ophthalmology

Table 6 Estimated logit coefficients from the multinomial logit model (coefficients and standard errors in brackets)

	Over/Underestimate logit
	Strategy 1	Strategy 2	Strategy 3	Strategy 4	Strategy 5
“Over” at average Mean IOP	−1.141***	0.648**	−0.408	−0.441	−0.167
	(0.346)	(0.285)	(0.279)	(0.282)	(0.258)
“Under” at average Mean IOP	−0.483*	−0.926**	−0.776**	−0.821***	−1.361***
	(0.272)	(0.452)	(0.313)	(0.318)	(0.393)
“Over” True Value Coefficient	0.137	0.080	0.104	−0.096	−0.011
	(0.095)	(0.100)	(0.083)	(0.092)	(0.079)
“Under” True Value Coefficient	0.052	0.355***	0.070	0.063	0.113
	(0.083)	(0.126)	(0.095)	(0.087)	(0.102)
Hits	36/70	21/70	33/70	33/70	33/70
Overestimates	12/70	38/70	22/70	22/70	28/70
Underestimates	22/70	11/70	15/70	15/70	9/70

The first two rows report the odds of Overestimates (first row) an Underestimate (second row) with respect to the Hits at the average Mean IOP value. The third and fourth rows report the logit coefficients for Over and Underestimate for the Mean IOP Value (i.e. how the odds vary with the real Mean IOP value). Asterisks represent the significance level according to the legend in the footnotes. The second half of the table reports the actual Hits, Over and Underestimate counts for each strategy
Note: *p < 0.1; **p < 0.05; ***p < 0.01

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