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1 s at baseline and week 4 were analyzed using multiple logistic regression.
2 s (aCFSs) to that of nonfragile sites, using multiple logistic regression.
3 ary outcome measures and were analyzed using multiple logistic regression.
4 aracteristics, and laboratory values using a multiple logistic regression.
5 ls for association with lung cancer by using multiple logistic regression.
6 -related hospitalization were examined using multiple logistic regression.
7 ficant correlation by using chi(2) tests and multiple logistic regression.
8 d at age of 6.5 years) were determined using multiple logistic regression.
9 d BRCAPRO models were assessed with stepwise multiple logistic regression.
10 the Fisher exact test, unpaired t tests, and multiple logistic regression.
11 dy (Virahep-C) were modeled using simple and multiple logistic regression.
12 ia-adenocarcinoma sequence were estimated by multiple logistic regression.
13 ical variables were analyzed with the use of multiple logistic regression.
14 rent atypical neuroleptics was examined with multiple logistic regression.
15                Statistical analysis included multiple logistic regression.
16 ed according to patient characteristics with multiple logistic regression.
17  as descriptive and correlation analyses and multiple logistic regression.
18 minants of readmission were identified using multiple logistic regression.
19 offspring peanut allergy were examined using multiple logistic regression.
20 rameters were assessed by means of linear or multiple logistic regressions.
21                                              Multiple logistic regressions adjusting for age, sex, Am
22 tions among these variables were examined by multiple logistic regression, adjusting for other CAD ri
23 in D and food allergy were examined by using multiple logistic regression, adjusting for potential ri
24 ir impact on outcome, using forward stepwise multiple logistic regression after adjusting for known p
25 iodontal variable was obtained from separate multiple logistic regression analyses adjusting for the
26 dependent variables was assessed by weighted multiple logistic regression analyses adjusting for the
27                               Univariate and multiple logistic regression analyses explored the progn
28 m weight retention at 6 mo were estimated by multiple logistic regression analyses for women in 3 cat
29                                              Multiple logistic regression analyses identified three i
30                            Ethnic-stratified multiple logistic regression analyses showed divergent r
31                                              Multiple logistic regression analyses showed that matern
32                                           In multiple logistic regression analyses that adjusted for
33 se, we used Kaplan-Meier, Cox regression and multiple logistic regression analyses to investigate the
34                                   Simple and multiple logistic regression analyses were conducted to
35                                              Multiple logistic regression analyses were conducted to
36                                              Multiple logistic regression analyses were done with eve
37                               Univariate and multiple logistic regression analyses were performed, an
38                              Univariable and multiple logistic regression analyses were performed, us
39                                              Multiple logistic regression analyses were used to compa
40                               Univariate and multiple logistic regression analyses were used to evalu
41                      Weighted chi2 tests and multiple logistic regression analyses were used to exami
42             Data were analyzed by linear and multiple logistic regression analyses, and the Mann-Whit
43                                           In multiple logistic regression analyses, independent deter
44                                  In adjusted multiple logistic regression analyses, metabolic syndrom
45                                        Using multiple logistic regression analyses, shared epitope al
46 ee periods were made by using univariate and multiple logistic regression analyses.
47 ions disappeared when controlling for sex in multiple logistic regression analyses.
48 onfidence intervals were determined by using multiple logistic regression analyses.
49                                              Multiple logistic-regression analyses showed that DNI wa
50                      Data analysis comprised multiple logistic regression analysis (case-control stud
51                                              Multiple logistic regression analysis (with generalized
52 R 4.37, 95% CI 1.41-13.54 [P = 0.010]) using multiple logistic regression analysis adjusting for age,
53                                           By multiple logistic regression analysis after adjusting fo
54                                              Multiple logistic regression analysis assessed the assoc
55                                           In multiple logistic regression analysis baseline cardiac i
56                                            A multiple logistic regression analysis combining the dose
57                                              Multiple logistic regression analysis confirmed the cont
58                                              Multiple logistic regression analysis demonstrated that
59                                        A new multiple logistic regression analysis demonstrated the a
60                                              Multiple logistic regression analysis estimated the inde
61                                              Multiple logistic regression analysis evaluated the asso
62 ew PBHs or the accumulation of PBHs, while a multiple logistic regression analysis evaluated the rela
63                                              Multiple logistic regression analysis for environmental
64                                              Multiple logistic regression analysis found that factors
65                                              Multiple logistic regression analysis identified inappro
66                                              Multiple logistic regression analysis identified non-idi
67                                              Multiple logistic regression analysis identified underly
68       Factors associated with depression via multiple logistic regression analysis included younger a
69                                     Based on multiple logistic regression analysis of PHS with adjust
70                                              Multiple logistic regression analysis of the complicatio
71                                              Multiple logistic regression analysis revealed an increa
72                                              Multiple logistic regression analysis revealed older age
73                                              Multiple logistic regression analysis revealed that male
74                                              Multiple logistic regression analysis revealed that the
75                                              Multiple logistic regression analysis revealed that, whe
76                                              Multiple logistic regression analysis showed that female
77                                              Multiple logistic regression analysis showed that high b
78                                              Multiple logistic regression analysis showed that increa
79                                              Multiple logistic regression analysis showed that infect
80                                              Multiple logistic regression analysis showed that the AL
81                                              Multiple logistic regression analysis showed that the pa
82                                              Multiple logistic regression analysis showed that the se
83                                              Multiple logistic regression analysis showed that visuos
84                                              Multiple logistic regression analysis showed that, after
85  sex, race/ethnicity, and geographic region; multiple logistic regression analysis to determine indep
86 y, and vessel volumetry, were used to feed a multiple logistic regression analysis to find significan
87                                              Multiple logistic regression analysis utilizing a linear
88                                              Multiple logistic regression analysis was applied to ide
89                                         When multiple logistic regression analysis was applied, this
90                                              Multiple logistic regression analysis was conducted to d
91                                              Multiple logistic regression analysis was performed; gen
92                                              Multiple logistic regression analysis was used to assess
93                                              Multiple logistic regression analysis was used to determ
94                                              Multiple logistic regression analysis was used to estima
95                                              Multiple logistic regression analysis was used to examin
96                                              Multiple logistic regression analysis was used to explor
97                                     Stepwise multiple logistic regression analysis was used to explor
98                                              Multiple logistic regression analysis was used to invest
99                                              Multiple logistic regression analysis was used to test f
100 k factors associated with eGFR <60 mL/min in multiple logistic regression analysis were age (P < 0.00
101  and European QOL 5D Visual Analog Scale via multiple logistic regression analysis were American regi
102                                         In a multiple logistic regression analysis, A1c >7% was a sig
103                                 We performed multiple logistic regression analysis, adjusting odds ra
104                                        After multiple logistic regression analysis, anti-PF4/heparin
105                                           In multiple logistic regression analysis, being overweight
106 ion of the two miRNAs together, tested using multiple logistic regression analysis, did not improve t
107                                           In multiple logistic regression analysis, elderly recipient
108                                           In multiple logistic regression analysis, NAFLD was the onl
109                              However, in the multiple logistic regression analysis, only EPE [odds ra
110                                           In multiple logistic regression analysis, only PTH increase
111                                           In multiple logistic regression analysis, predicted extrava
112  education, and first-trimester exposures in multiple logistic regression analysis, the authors found
113                                           In multiple logistic regression analysis, the prevalence of
114                                           By multiple logistic regression analysis, we found that the
115 ce of at least one of the applicable PSIs on multiple logistic regression analysis, with confirmation
116 sted for a number of possible confounders in multiple logistic regression analysis.
117 ween periodontal disease and PH on bivariate multiple logistic regression analysis.
118     Independent factors were identified with multiple logistic regression analysis.
119  those without CIN by using forward stepwise multiple logistic regression analysis.
120 versus advanced fibrosis) were explored with multiple logistic regression analysis.
121 e were independently associated with CDAD by multiple logistic regression analysis.
122 ndependent of pack-year smoking history with multiple logistic regression analysis.
123  associated with outcome were entered into a multiple logistic regression analysis.
124 e only independent predictor of mortality on multiple logistic regression analysis.
125 ferences in CT features were identified with multiple logistic regression analysis.
126 dverse events by using Fisher exact test and multiple logistic regression analysis.
127 aediatric Index of Mortality, and surgeon on multiple logistic regression analysis.
128 ors for utilization of dental services using multiple logistic regression analysis.
129                                       In our multiple logistic-regression analysis, consumption of ra
130                                              Multiple logistic-regression analysis, with the use of t
131                                    Bivariate multiple logistic regression and adjusted prevalence ana
132                                              Multiple logistic regression and analysis of covariance
133                                              Multiple logistic regression and Cox proportional hazard
134               Nonparametric tests as well as multiple logistic regression and mixed effects logistic
135          Associations were assessed by using multiple logistic regression and subsequent meta-analysi
136 attributable fractions were derived by using multiple logistic regression and the Levin formula.
137                                              Multiple logistic regression and Tobit regression models
138  developing severe renal insufficiency using multiple logistic regression, and the predictive ability
139                                              Multiple logistic regression assessed odds ratio for sur
140                                              Multiple logistic regression (c-statistic 0.715, 95% CI:
141  months before interview were obtained using multiple logistic regression controlling for demographic
142 h out-of-pocket expenses were estimated from multiple logistic regression controlling for demographic
143 each microorganism with CAL was tested using multiple logistic regressions controlling for age, smoki
144 28-day survivors, using Bonferroni-corrected multiple logistic regression, days alive and free of ven
145                                              Multiple logistic regression demonstrated a significant
146                                              Multiple logistic regression demonstrated an increased r
147                                              Multiple logistic regression demonstrated the following
148                                              Multiple logistic regressions demonstrated that an open
149                       Using the best-fitting multiple logistic regression equation, a 100-point incre
150                                        Using multiple logistic regression, five features were indepen
151                                    They used multiple logistic regression for their comparison.
152  after simultaneously controlling (by use of multiple logistic regression) for age, gender and cardia
153                                              Multiple logistic regression identified having an OC, ag
154                                              Multiple logistic regression identified independent risk
155       Independent risk factors identified in multiple logistic regression included chorioamnionitis (
156 rminants of neoatherosclerosis identified by multiple logistic regression included younger age (p < 0
157                                        Using multiple logistic regression, increased eNO (odds ratio,
158                                           By multiple logistic regression, independent risk factors f
159                                           At multiple logistic regression, kurtosis on T2-weighted im
160                                           On multiple logistic regression, LVOT gradient reduction af
161                                      ANN and multiple-logistic-regression (MLR) models were construct
162                                            A multiple logistic regression model (c-statistic 0.657, 9
163 to identify predictors of service use with a multiple logistic regression model and predictors of cos
164                                              Multiple logistic regression model confirmed that endoth
165            The second approach constructed a multiple logistic regression model considering significa
166                                            A multiple logistic regression model including standard Fr
167                                            A multiple logistic regression model incorporating oxygena
168                                            A multiple logistic regression model predicting odds of su
169                                            A multiple logistic regression model revealed independent
170                                            A multiple logistic regression model that included predict
171  found to be significant were entered into a multiple logistic regression model to identify factors i
172  tooth-level multivariate survival model and multiple logistic regression model using the method of g
173                                            A multiple logistic regression model was estimated at impl
174                                            A multiple logistic regression model was then developed to
175                                            A multiple logistic regression model was used to evaluate
176                                            A multiple logistic regression model was used to identify
177                               Two types of a multiple logistic regression model were fit: 1) logistic
178            Adjusted odds ratios (ORs) from a multiple logistic regression model were used to estimate
179                                         In a multiple logistic regression model with patients aged 65
180 s with bivariate analyses and constructing a multiple logistic regression model with the number of po
181 s examined using a univariate analysis and a multiple logistic regression model, adjusting for age, s
182                                         In a multiple logistic regression model, African American rac
183 pregnancy physical activity, and income in a multiple logistic regression model, regular use of multi
184                                         In a multiple logistic regression model, risks of incident hy
185                                         In a multiple logistic regression model, the G allele was ass
186                                         In a multiple logistic regression model, the OR for HLA-B*27:
187 r adjustment for significant covariates in a multiple logistic regression model, the use of OSP was a
188                                         In a multiple logistic regression model, there was a signific
189 ingle regressor analysis were entered into a multiple logistic regression model.
190 iate predictors of death were entered into a multiple logistic regression model.
191  analyzed thereafter in a backward selection multiple logistic regression model.
192                            Using a two-stage multiple-logistic regression model, we found association
193                                              Multiple logistic regression modeling and propensity sco
194                                              Multiple logistic regression modeling quantified the ass
195                                              Multiple logistic regression modeling showed the effect
196                                              Multiple logistic regression modeling was used to identi
197                       Bivariate analyses and multiple logistic regression modeling were performed.
198               In rejection episode analyses, multiple logistic regression modelling showed that chang
199                                              Multiple logistic regression models adjusted for subject
200                                              Multiple logistic regression models analyzed all variabl
201                                              Multiple logistic regression models for case-control dat
202 , lifestyle, and sociodemographic factors in multiple logistic regression models for prediction of th
203 e best predicting parameter of CA diagnosis (multiple logistic regression models P<0.00005 and P=0.00
204                                              Multiple logistic regression models revealed that combin
205                                              Multiple logistic regression models showed that children
206 smoke exposure with ADHD was examined by two multiple logistic regression models that differ in the s
207                                      We used multiple logistic regression models to adjust for age, s
208                                      We used multiple logistic regression models to examine the effec
209                                     Adjusted multiple logistic regression models were applied to asse
210                                              Multiple logistic regression models were developed to ex
211                                         When multiple logistic regression models were fit with adjust
212                                              Multiple logistic regression models were fitted to calcu
213 vidually assessed at the genotype level, and multiple logistic regression models were used to adjust
214  patient characteristics was determined, and multiple logistic regression models were used to adjust
215            Generalized linear regression and multiple logistic regression models were used to assess
216                                              Multiple logistic regression models were used to assess
217 nquired about "self-assessed periodontitis." Multiple logistic regression models were used to constru
218                                              Multiple logistic regression models were used to examine
219                                        Three multiple logistic regression models were used to generat
220                                              Multiple logistic regression models were used to identif
221  CI: 0.88, 1.02 (P = 0.16), respectively] in multiple logistic regression models with adjustment for
222 ompliance were then evaluated in a series of multiple logistic regression models with adjustment for
223                     Data were analyzed using multiple logistic regression models with backward stepwi
224                                           In multiple logistic regression models, both treatment and
225 rvals (CIs) were obtained from unconditional multiple logistic regression models, including terms for
226                                       In the multiple logistic regression models, the median glycemic
227                                              Multiple logistic regression models, with tooth-level bl
228                Risk factors were examined in multiple logistic regression models.
229 laining 70% of the variance were included in multiple logistic regression models.
230 e adjusted for patient characteristics using multiple logistic regression models.
231 from 2002-2008 were examined in detail using multiple logistic regression (n = 774,399).
232                                           In multiple logistic regression, odds of oral HPV infection
233 association was independently significant in multiple logistic regression (P = 0.04) along with race,
234                                              Multiple logistic regression revealed that females were
235                                              Multiple logistic regression revealed that the CYP11B2 -
236                                              Multiple logistic regressions revealed that both Fcgamma
237                                              Multiple logistic regression showed independent associat
238                                     Weighted multiple logistic regressions showed that this relations
239        After adjustment for covariates using multiple logistic regression, significantly more African
240 redictive than another using ROC curves, but multiple logistic regression suggested salT was more pre
241 re compared between cases and controls using multiple logistic regression techniques.
242                  Student t test, chi(2), and multiple logistic regression tests were performed as app
243                                           By multiple logistic regressions, the following association
244 al abnormalities and asbestos exposure using multiple logistic regression to adjust for year of birth
245                                      We used multiple logistic regression to assess differences in op
246                                      We used multiple logistic regression to assess relationships bet
247                                      We used multiple logistic regression to assess the association b
248                             The authors used multiple logistic regression to assess the relation betw
249                                      We used multiple logistic regression to determine the independen
250                                      We used multiple logistic regression to estimate associations be
251                                      We used multiple logistic regression to estimate odds ratios (OR
252                                      We used multiple logistic regression to estimate predictive marg
253                       We used univariate and multiple logistic regression to examine clinical and lab
254                                      We used multiple logistic regression to investigate whether mild
255                                      We used multiple logistic regressions to evaluate clinical and s
256                                           In multiple logistic regression, transplant status was inde
257                                           In multiple logistic regression, urinary NGAL level was hig
258                      Data were analyzed in a multiple logistic regression using MoCA scores suggestiv
259                                              Multiple logistic regression using robust standard error
260                                         When multiple logistic regression was applied to the data, th
261                                              Multiple logistic regression was performed to analyze th
262                                              Multiple logistic regression was performed to compare di
263                                              Multiple logistic regression was performed to study the
264                                              Multiple logistic regression was performed using a discr
265 pation by self-administration of the survey, multiple logistic regression was performed.
266 ndent risk factors for hospital mortality by multiple logistic regression was rupture (P<0.0009), and
267                                              Multiple logistic regression was used to assess the effe
268                                              Multiple logistic regression was used to assess the inde
269                                              Multiple logistic regression was used to assess the use
270                                              Multiple logistic regression was used to assess the use
271                                              Multiple logistic regression was used to calculate odds
272                                     Stepwise multiple logistic regression was used to calculate the o
273                                              Multiple logistic regression was used to compare anemia
274                                              Multiple logistic regression was used to determine signi
275                                              Multiple logistic regression was used to determine the i
276                                              Multiple logistic regression was used to determine the r
277          Adjusting for student demographics, multiple logistic regression was used to determine wheth
278 aseline who continued to drive at follow-up, multiple logistic regression was used to estimate the od
279                                              Multiple logistic regression was used to examine associa
280                                              Multiple logistic regression was used to examine the ind
281                                              Multiple logistic regression was used to examine the rel
282                                            A multiple logistic regression was used to explore the com
283                                              Multiple logistic regression was used to identify factor
284                                              Multiple logistic regression was used to identify factor
285                                              Multiple logistic regression was used to identify indepe
286                                            A multiple logistic regression was used to identify indepe
287                                              Multiple logistic regression was used to identify risk f
288                                              Multiple logistic regression was used to measure the ass
289                                              Multiple logistic regression was used to measure the imp
290                                              Multiple logistic regression was used to quantify the ef
291                                              Multiple logistic regression was used to test hypotheses
292                                              Multiple logistic regression was used with mortality as
293 son chi-square tests, Fisher exact test, and multiple logistic regression, was performed.
294                                        Using multiple logistic regression, we explored the associatio
295                                        Using multiple logistic regression, we identified significant
296            Random Forests classification and multiple logistic regression were used to assess the RI
297         Weighted population, prevalence, and multiple logistic regression were used.
298                       Bivariate analysis and multiple logistic regressions were performed to identify
299                                              Multiple logistic regressions were used to derive adjust
300                                              Multiple logistic regression, with adjustments for demog

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