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Table 4 Parameter estimation of id2 versus id4

From: Regression models for analyzing radiological visual grading studies – an empirical comparison

Model GWscore GQscore BGscore
Est. P-value Est. P-value Est. P-value
regressa −0.050 0.199 −0.017 0.641 −0.054 0.141
(−0.126, 0.026) (−0.087, 0.054) (−0.126, 0.018)
ologita −0.322 0.164 −0.13 0.603 −0.374 0.127
(−0.775, 0.131) (−0.621, 0.361) (−0.854, 0.107)
gologit2a −0.215 0.488 −0.393 0.185 −0.596 0.046
=2 (−0.823, 0.392) (−0.975, 0.189) (−1.182, −0.010)
gologit2a −0.472 0.182 0.629 0.228 0.104 0.82
=3 (−1.166, 0.221) (−0.394, 1.653) (−0.788, 0.996)
slogita −0.592 0.194 −0.408 0.281 −0.743 0.052
(−1.485, 0.301) (−1.150, 0.334) (−1.491, 0.005)
mixedb −0.050 0.176 −0.017 0.640 −0.054 0.14
(−0.122, .022) (−0.087, 0.053) (−0.126, 0.018)
meologitb −0.3217 0.164 −0.126 0.598 −0.336 0.152
(−0.775, 0.131) (−0.597, 0.344) (−0.794, 0.123)
  1. 95 % confidence limits given in parentheses
  2. aregression model with fixed effects only
  3. bregression model with fixed and random effects