Changes in experimental eyes and fellow eyes over the 3-day-long experiments are summarized in
Table 1 . Because we were specifically interested in the changes during the course of the treatment, we used relative change (the change in the experimental eye over the course of the experiment minus the change in the fellow eye) to represent the net effect of the lens wear. The relative changes that were significantly different from 0 by paired, two-tailed Student’s
t-tests are shown in
Table 1 . Relative change is plotted against either the duration of the lens-wearing episodes for rise-time in experiment 1
(Fig. 3)or the dark interval between lens-wearing episodes for fall-time in experiment 2
(Fig. 4) , both on logarithmic scales, so that different time points are nearly evenly separated. Analysis of variance (ANOVA) with LSD post hoc tests was used to compare the relative changes among various episode durations (for experiment 1) or dark intervals between episodes (for experiment 2).
Data of the individual birds of each experiment were fitted (using Igor Pro version 5.02; WaveMetrics, Inc, Lake Oswego, OR) with a sigmoidal curve of the form y = y o + Δy/(1 + exp(x 0−x)/z ), with x being the logarithm of the episode duration or interval. The coefficient y o is the y value at small x, (y o + Δy) is the y value at large x, x 0 is the log of the x value at which y is midway between the low and high y asymptotes (i.e., the rise- or fall-times), and z is the rate of rise or fall. The 95% confidence intervals (CIs) for x 0 were also calculated. In some cases, the unconstrained curve-fitting yielded implausible confidence intervals. Therefore, in all cases, we performed three successive fits to yield x 0, the primary parameter of interest: First, we limited the ranges of y o and Δy and let the algorithm fit these 2 parameters to yield the fitted values for y o and Δy; second, we fixed y o and Δy at the their fitted values and let the algorithm fit the optimal value for z; and third, we fixed y o, Δy, and z at their fitted values and let the algorithm obtain the value for x 0 and its 95% CI. Because x 0 was calculated as a logarithm, the 95% CI was asymmetric when converted into minutes or hours.