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1 e to settings where the exposure variable is polytomous and where the assumption of independence betw
2 atment is dichotomous, treatment is actually polytomous as there are at least 3 levels: no treatment,
3 ferent morphological habitus, including long polytomous body branches and a maximum body length of mo
4          When one estimates the effects of a polytomous exposure, it is common practice to express al
5 lassic (Levin's) epidemiological formula for polytomous exposures, with relative risks (RRs) reported
6                                          The polytomous logistic regression (PLR) model provides a fl
7 ted the biomarker panel to LV geometry using polytomous logistic regression adjusting for clinical co
8 h case-only logistic regression analyses and polytomous logistic regression analyses (with one contro
9 f a mutation in any of the LS genes by using polytomous logistic regression analysis of clinical and
10                                Multivariable polytomous logistic regression and canonical discriminan
11                                              Polytomous logistic regression and Wald tests for hetero
12                                              Polytomous logistic regression evaluated associations wi
13    In this paper, the authors describe how a polytomous logistic regression method previously develop
14                              A multivariable polytomous logistic regression model (PREMM(1,2,6)) was
15                                              Polytomous logistic regression models assessed relations
16                                              Polytomous logistic regression models were used to asses
17                                              Polytomous logistic regression models were used to estim
18                                              Polytomous logistic regression models were used to estim
19                                              Polytomous logistic regression models were used to evalu
20                                              Polytomous logistic regression models with a random inte
21 ral log-1 unit increase) were assessed using polytomous logistic regression models, joint effects usi
22                              In multivariate polytomous logistic regression models, medically indicat
23                                           In polytomous logistic regression models, parity and age at
24  (OFI), and apparent DENV using multivariate polytomous logistic regression models.
25                                              Polytomous logistic regression procedures were used to d
26                            This quantitative polytomous logistic regression test allows for analysis
27 authors propose an extension to quantitative polytomous logistic regression that allows testing for m
28                                 We performed polytomous logistic regression to calculate odds ratios
29                        We used multivariable polytomous logistic regression to compare case groups wi
30                                      We used polytomous logistic regression to estimate odds ratios (
31 p but not enrollment (n = 688; 40%) and used polytomous logistic regression to estimate odds ratios (
32 to investigate etiologic heterogeneity or do polytomous logistic regression to estimate odds ratios s
33 egorical outcome typically entails fitting a polytomous logistic regression via maximum likelihood es
34                                              Polytomous logistic regression was performed to estimate
35                                    Unordered polytomous logistic regression was used to calculate adj
36                                 Multivariate polytomous logistic regression was used to calculate odd
37                                Multivariable polytomous logistic regression was used to estimate odds
38                                              Polytomous logistic regression was used to estimate odds
39                                              Polytomous logistic regression was used to estimate ORs
40                                              Polytomous logistic regression was used to estimate the
41                                 Logistic and polytomous logistic regression were used to estimate odd
42    Factors associated with surgery use (from polytomous logistic regression); overall and breast canc
43 analyses to support differences in risk: (1) polytomous logistic regression, (2) homogeneity tests, o
44                                    By use of polytomous logistic regression, factors possibly influen
45 ype-specific associations with multivariable polytomous logistic regression.
46 articipants with concordant data via 2-sided polytomous logistic regression.
47  the common control group through the use of polytomous logistic regression.
48 25(OH)D using stepwise linear regression and polytomous logistic regression.
49 % confidence intervals were calculated using polytomous logistic regression.
50 entional) were estimated using multivariable polytomous logistic regressions and multilevel models.
51                                              Polytomous logistic regressions were used to estimate OR
52                                         This polytomous model selection approach can be used to ident
53 e control group examined by colonoscopy in a polytomous model with several case groups (newly diagnos
54                                        Using polytomous multiple logistic regression, the authors fou
55 ype, for example, binary, count, continuous, polytomous, ordinal, time-to-onset, multivariate and oth
56 ment before and after rehabilitation, by the polytomous rating scale measurement model of Wright and
57         In this paper, we show that standard polytomous regression is ill equipped to detect outcome
58                                      We used polytomous regression models adjusted for age, BMI, stat
59                   Specifically, nonsaturated polytomous regression will often a priori rule out the p
60                                           In polytomous regression, odds ratios for BMI (P = 0.65), s
61 atios were estimated by race/ethnicity using polytomous regression.
62 vals (CIs) were estimated using logistic and polytomous regression.
63   A three-parameter logistic model (3PL) for polytomous response was calculated to evaluate a model o
64 bias away from the null; and, if exposure is polytomous, the bias produced by independent nondifferen
65 ngness, and trajectories were modelled using polytomous variable latent class analysis (poLCA) in bot