1 after ileal compared to cecal intubation in
univariate (
12.5% vs. 6.8%, p < 0.001, and 6.3% vs. 3.3%
2 Moreover, both
univariate activation in mPFC and multivariate self-othe
3 data (n = 10), selecting variables based on
univariate analyses (n = 9), overfitting (n = 13), and l
4 hout the study in regression models, both in
univariate analyses (regression coefficient -7.07, 95% C
5 l and progesterone each related to autism in
univariate analyses after correction with false discover
6 We performed
univariate analyses and Cox regression analyses includin
7 Univariate analyses and generalized linear regression mo
8 Univariate analyses and machine learning techniques were
9 Univariate analyses determined that females had a 40% hi
10 Univariate analyses of texture features showed that code
11 Our
univariate analyses revealed that all tastes (vs tastele
12 Univariate analyses showed a significant main effect of
13 Univariate analyses showed that WB-MATV and WB-TLG param
14 n analyses including important predictors on
univariate analyses to determine independent predictors
15 Univariate analyses were performed to assess the prognos
16 This is benign for
univariate analyses where only variants with large effec
17 ficult bag-mask ventilation were found using
univariate analyses, and multivariable logistic regressi
18 In
univariate analyses, factors such as baseline PSA, any P
19 , AFNI, FSL, SPM) focus on preprocessing and
univariate analyses, leaving a gap in how to integrate w
20 In
univariate analyses, loss of regular isopachs (hazard ra
21 In
univariate analyses, lower BMI and oxidized LDL, and hig
22 In
univariate analyses, lower BMI and oxidized LDL, and hig
23 In
univariate analyses, monitoring was associated with redu
24 However, these studies have relied on
univariate analyses, reducing power and limiting context
25 coefficients, respectively (P < 0.0001), in
univariate analyses.
26 l associated with higher (i.e. worse) HMS in
univariate analyses; CVD and ARCD persisted in multivari
27 ll associated with higher (ie, worse) HMS in
univariate analyses; CVD and ARCD persisted in multivari
28 = 0.07), patients with PNI had worse DFS at
univariate analysis (median DFS: 20 vs 15 months, P < 0.
29 s significantly associated with mortality in
univariate analysis (odds ratio = 1.08 per mmol/L glucos
30 nificantly associated with mortality both in
univariate analysis (odds ratio = 1.09 per 0.1 stress hy
31 and St George's Respiratory Questionnaire at
univariate analysis (P < .001 for each).
32 ted with poor disease free survival (DFS) in
univariate analysis (p = 0.056).
33 ivariate adjustment compared to studies with
univariate analysis (RR 2.15 [1.27-3.64] vs. 1.15 [0.88-
34 In development, a third of models used
univariate analysis alone to identify statistically sign
35 Univariate analysis and LEfSE showed a lower abundance o
36 Univariate analysis and multivariate logistic regression
37 , MetS, and periodontitis was tested through
univariate analysis and multivariate logistic regression
38 On
univariate analysis at 5 years, a lower CCECD was associ
39 Univariate analysis compared outcomes overall and at ind
40 horter in the transcutaneous biopsy group on
univariate analysis compared to the other groups; howeve
41 Univariate analysis demonstrated differences between con
42 Univariate analysis did not show a statistically signifi
43 For all biopsies,
univariate analysis found that failure was strongly asso
44 Univariate analysis identified age, International Stagin
45 Univariate analysis identified higher ISCM size (p=0.024
46 Univariate analysis identified serum bilirubin, alkaline
47 A
univariate analysis of male and female carriers of the T
48 After conducting
univariate analysis of risk factors, statistically signi
49 Univariate analysis of severe POM and multiple secondary
50 Univariate analysis of this 107 DEP gene signature in pr
51 Univariate analysis of uncontrolled DCD-specific risk fa
52 ong animal- and plant-based samples, one-way
univariate analysis of variance followed by pair-wise co
53 Univariate analysis revealed robust category-selective r
54 Univariate analysis revealed significant MS peaks in the
55 A
univariate analysis revealed that age <40 years (n = 89;
56 Univariate analysis revealed the mechanism not to be ass
57 205 listings (27 393 pre-PAS; 24 439 T2DM),
univariate analysis showed reduced percentages for SPK p
58 Univariate analysis showed that age at transplantation;
59 Univariate analysis showed that fractionated total body
60 Univariate analysis showed that higher ART grades were s
61 In the TIME trial,
univariate analysis showed that MIE reduced pulmonary co
62 Univariate analysis shows that statistically significant
63 chnique (P = 0.008) were risk factors in the
univariate analysis using Cox regression models, whereas
64 Univariate analysis was performed to compare pseudophaki
65 Univariate analysis was undertaken based on age, vaccina
66 Univariate analysis was used to compare baseline charact
67 Univariate analysis was used to determine the associatio
68 ning set, variables found significant in the
univariate analysis were fed into a multivariate regress
69 [31 of 73] vs 57.8% [52 of 90]; P = .053 by
univariate analysis).
70 R = 1.66 [95% CI: 1.05-2.61]; p = 0.0291) at
univariate analysis, but not at the multivariate analysi
71 greater odds of showing advanced glaucoma in
univariate analysis, but not in multivariate analyses.
72 ne use was negatively associated with SVR in
univariate analysis, but this association was not signif
73 On
univariate analysis, early recurrence was associated wit
74 RSI analysis was conducted using a
univariate analysis, fitting unique plastic bands to the
75 for all variables showing the association in
univariate analysis, HCM itself remained a robust predic
76 In the
univariate analysis, HGAIN was associated with CT, UU, M
77 In
univariate analysis, higher AF genetic susceptibility tr
78 In
univariate analysis, no patient or tumor feature was ass
79 In
univariate analysis, none of the clinical variables, 2 P
80 In
univariate analysis, none of the clinical variables, 2 P
81 In a
univariate analysis, older age, higher pre-procedure pai
82 Compared to
univariate analysis, partial least squares improves typi
83 On
univariate analysis, pre-HCT AIC, mismatched donor, alem
84 In
univariate analysis, rate of recurrence was reduced when
85 Conclusions In
univariate analysis, the number of coronary arteries dis
86 In
univariate analysis, UMI and RMI were strongly associate
87 On
univariate analysis, White children had higher mortality
88 On
univariate analysis, young age, no statin use, history o
89 of postoperative double AC formation in the
univariate analysis.
90 hat were significant at the 0.2 level in the
univariate analysis.
91 r rates of seizure recurrence (p = 0.004) in
univariate analysis; however, its predictive value did n
92 ere analyzed using linear mixed models, both
univariate and adjusted for social and maternal factors.
93 ized (thick vs thin subarachnoid hemorrhage)
univariate and adjusted logistic regression models to as
94 Similar results were obtained with
univariate and bivariate regression models for predictio
95 exact, t test, or Wilcoxon rank sum test for
univariate and logistic regression for multivariate anal
96 Univariate and multivariable analyses were performed by
97 Univariate and multivariable analyses were performed.
98 Univariate and multivariable analyses were used to deter
99 d prespecified risk factors were tested in a
univariate and multivariable analyses, with an endpoint
100 tions with outcome measures were explored in
univariate and multivariable analyses.
101 Descriptive statistics,
univariate and multivariable Cox proportional hazards re
102 Operation-specific
univariate and multivariable logistic regression analyse
103 We used
univariate and multivariable logistic regression to dete
104 onducted in 2006 using descriptive analyses,
univariate and multivariable regression methods.
105 Univariate and multivariable techniques were used to com
106 Univariate and multivariate (MV) analyses were performed
107 Moreover, in
univariate and multivariate analyses (adjusted to Fuhrma
108 Univariate and multivariate analyses also identified hig
109 Univariate and multivariate analyses confirmed that PD-L
110 Univariate and multivariate analyses identified histopat
111 We combine
univariate and multivariate analyses of fMRI data from a
112 male and female human participants combines
univariate and multivariate analyses to consider the cor
113 erall survival of these patients and applied
univariate and multivariate analyses to derive the risk
114 We used
univariate and multivariate analyses to investigate the
115 Univariate and multivariate analyses were performed to a
116 entral retinal vein occlusion (CRVO) cohort,
univariate and multivariate analyses were performed to i
117 Both
univariate and multivariate analyses were performed to i
118 Univariate and multivariate analyses were performed usin
119 Univariate and multivariate analyses were then performed
120 Univariate and multivariate analyses were used to determ
121 Univariate and multivariate analyses were used to identi
122 Univariate and multivariate analyses with Cox regression
123 ical variables as predictors of survival, in
univariate and multivariate analyses.
124 ted with shorter cumulative survival in both
univariate and multivariate analyses.
125 t was negatively associated with PFS in both
univariate and multivariate analyses.
126 on were assessed using Poisson regression in
univariate and multivariate analyses.
127 B2 mRNA levels had better 5-year survival in
univariate and multivariate analysis (P = 0.031 and P =
128 had a significantly lower rate of LE both in
univariate and multivariate analysis [3% vs 19%; P = 0.0
129 Univariate and multivariate analysis of fMRI data reveal
130 We used
univariate and multivariate analysis to explore value en
131 nfrared (uATR-FTIR) spectroscopic mapping by
univariate and multivariate analysis was applied for stu
132 Univariate and multivariate analysis were carried out to
133 Univariate and multivariate analysis were performed to d
134 On
univariate and multivariate analysis, patient survival w
135 nd potential risk variables were analyzed by
univariate and multivariate analysis, when appropriate.
136 dictive factors of survival were analyzed by
univariate and multivariate analysis.
137 and medication adherence was assessed using
univariate and multivariate analysis.
138 face (ox-GCE-[AuNPs-SiPy]) were optimized by
univariate and multivariate analysis.
139 using other model-free approaches as well as
univariate and multivariate autoregressive models using
140 We combined
univariate and multivariate brain imaging analyses to as
141 determined within 120-140 s using different
univariate and multivariate calibration approaches.
142 Univariate and multivariate calibrations were assessed f
143 Univariate and multivariate Cox analyses were used to as
144 Univariate and multivariate Cox proportional hazard regr
145 Univariate and multivariate Cox proportional hazards ana
146 Univariate and multivariate Cox proportional hazards ana
147 Univariate and multivariate Cox regression analyses were
148 Univariate and multivariate Cox regression analysis were
149 Univariate and multivariate Cox regression was used to e
150 Data modeling was based on
univariate and multivariate data analyses.
151 We systematically investigated
univariate and multivariate feedback encoding in various
152 Using
univariate and multivariate fMRI analyses (n = 65), we e
153 exception of the same two individuals, both
univariate and multivariate fMRI analyses revealed norma
154 articipant-specific behavioral modeling with
univariate and multivariate fMRI approaches, we investig
155 l variables on MBLs changes was assessed via
univariate and multivariate generalized estimating equat
156 Univariate and multivariate generalized linear models we
157 Herein, we assess predictive abilities of
univariate and multivariate genomic prediction models in
158 factors with retinopathy were assessed using
univariate and multivariate linear and logistic regressi
159 Univariate and multivariate logistic regression analyses
160 Univariate and multivariate logistic regression analyses
161 Univariate and multivariate logistic regression analyses
162 Univariate and multivariate logistic regression analysis
163 Univariate and multivariate logistic regression models w
164 We performed
univariate and multivariate logistic regression to evalu
165 Univariate and multivariate logistic regression was perf
166 Univariate and multivariate logistic regression were use
167 Univariate and multivariate logistic regressions were pe
168 We also briefly compare and discuss
univariate and multivariate methods for brain-behaviour
169 Univariate and multivariate methods were used to compare
170 ds achieve a higher performance than classic
univariate and multivariate methods, supporting the hypo
171 y antigen, associated with graft failure, in
univariate and multivariate models (hazard ratio = 2.7;
172 -treat analysis were included in exploratory
univariate and multivariate models for overall survival
173 eir outcomes to the rest of the cohort using
univariate and multivariate models.
174 eedback information (partial vs complete) on
univariate and multivariate outcome value encoding, with
175 e brain, these behavioral effects related to
univariate and multivariate parametric effects in the MT
176 l and subcortical abnormalities in both mass-
univariate and multivariate pattern recognition analyses
177 Univariate and multivariate Poisson regression models we
178 Univariate and multivariate regression analyses were per
179 Univariate and multivariate regression analyses were use
180 Univariate and multivariate regression models were fitte
181 Associations were tested with
univariate and multivariate regression models.
182 thickness measurements were evaluated using
univariate and multivariate regression models.
183 During proactive control, both
univariate and multivariate signals of beta-band (15-35
184 ome and microbiome, from data preprocessing,
univariate and multivariate statistical analyses, advanc
185 light mass spectrometry (HPLC-Q-TOF MS) with
univariate and multivariate statistical analyses.
186 Univariate and multivariate statistical analysis overlap
187 Complementary
univariate and multivariate statistical methods were use
188 s predictive of recovery were evaluated with
univariate and multivariate statistical tests.
189 on survival was evaluated subsequently using
univariate and multivariate survival estimates.
190 Complementary
univariate and multivariate techniques characterized spe
191 eline method of listwise deletion to classic
univariate and multivariate techniques.
192 Univariate and multivariate, including propensity-adjust
193 quipment, maintenance, and training, and did
univariate and probabilistic sensitivity analyses for UA
194 Demographics were compared, and
univariate and risk-adjusted analyses evaluated the rela
195 yses with cumulative incidence functions and
univariate Andersen-Gill regression for primary outcomes
196 A dual criterion based on
univariate (
ANOVA) and multivariate analysis (PLS-DA) th
197 restricted to a multivariate compared with a
univariate approach, and to be specific for valence proc
198 emory performance, but has relied heavily on
univariate approaches (averaging activity across hippoca
199 diographic loci unapparent using traditional
univariate approaches, although this approach did assist
200 ficant predictors of SSTI incidences in both
univariate as well as multivariate analyses included a l
201 fferent between eyes with and without DME in
univariate assessment.
202 r safety or effectiveness) had the strongest
univariate association with vaccine uptake compared with
203 and sources of trust, were determined using
univariate Bayesian logistic regressions.
204 an systems yet are less well documented than
univariate changes.
205 artures that were nearly three times that of
univariate climate departures across global lands.
206 o map such patterns, we introduce a weighted
univariate clustering algorithm to guarantee linear runt
207 tive network for the high-SES versus low-SES
univariate comparison.
208 ication of the minimum P value approach with
univariate competing risk regressions (deceased donor li
209 thods for functional brain imaging-including
univariate contrast, searchlight multivariate pattern cl
210 s was always superior in comparison to their
univariate counterparts.
211 Recursive partitioning with
univariate Cox models of event-free survival ("survival
212 Through the
univariate Cox proportional hazards analysis, common gen
213 Univariate Cox regression analyses detected age, waist-t
214 In
univariate Cox regression analyses, estimated glomerular
215 y associated with all-cause mortality in the
univariate Cox regression analysis (hazard ratio, 1.09 [
216 Methods based on
univariate Cox regression are often used to select genom
217 as validated using the concordance index for
univariate Cox regression models determined from the tra
218 ortality (HR 0.67, 95%CI: 0.45-0.98) only by
univariate Cox regression.
219 assessed alpha-band modulation with massive
univariate deconvolution, an analysis approach that dise
220 e climate departures have generally outpaced
univariate departures in recent decades.
221 ic bootstrapping to assess uncertainties and
univariate deterministic sensitivity analysis to examine
222 ed with postoperative PVR were determined by
univariate feature selection.
223 ucted multivariable-adjusted, trait-specific
univariate genome-wide association studies using 1000-G
224 alue of our multivariate methods relative to
univariate GWAMA.
225 ot previously identified in the contributing
univariate GWASs.
226 Univariate hazard ratio (HR) of CTC-positivity was 3.4 (
227 ality was substantial for severe arrhythmia (
univariate hazard ratio [HR]: 2.70; 95% confidence inter
228 rth-quartile range than in the first, with a
univariate hazard ratio of 6.2 (95% CI, 2.8-13.6; P < 0.
229 with an increased risk of developing HCC in
univariate (
hazard ratio [HR] = 3.6; 95% confidence inte
230 ificant predictor of PC-specific survival in
univariate (
hazard ratio, 3.75; P < 0.001) and multivari
231 with an increased risk of developing HCC in
univariate (
HR = 1.4; 95% CI = 1.1-1.8; P < 0.01) and mu
232 ue positive, false positive, negative) using
univariate (
ie, Fisher exact) and multivariate machine l
233 In contrast to existing
univariate linear mixed model analyses, the proposed met
234 predictors with each of the response using a
univariate linear regression model, and to select predic
235 Univariate linear regressions were performed within each
236 Univariate log rank, and multivariable Cox analyses dete
237 hich prenatal androgens were measured, using
univariate logistic regression (n = 98 cases, n = 177 co
238 Univariate logistic regression analyses were performed t
239 tabolome-AMD associations were studied using
univariate logistic regression analyses.
240 Univariate logistic regression analysis revealed that an
241 According to
univariate logistic regression analysis, MetS was signif
242 Univariate logistic regression was used to assess factor
243 Univariate logistic regression was used to compare outco
244 and average whole-brain FA were entered into
univariate mega- and meta-analyses to differentiate pati
245 detect small-study effects in the results of
univariate meta-analyses.
246 y for microbiome analysis did not outperform
univariate methods developed for differential expression
247 Data were analyzed using
univariate methods.
248 n largely limited to inferring thresholds in
univariate metrics of species richness and indices of bi
249 h county-level prevalence of diabetes in the
univariate model (odds ratio, 1.12; 95% CI, 1.06-1.19; P
250 A Kaplan-Meier estimate with a
univariate model determined the impact of CA on cardiac
251 GS (hazard ratio [HR], 2.35; P < 0.001) in a
univariate model, on the full analysis set comprising 10
252 Univariate models did not yield any association between
253 Univariate models of the individual DHIs had lower predi
254 In
univariate models, CP (P = 0.034), CHD (P < 0.001), and
255 We found that household income (
univariate MR: beta = -0.22, p = 1.57 x 10(-7); multivar
256 a = -0.17, p = 0.005) and deprivation index (
univariate MR: beta = 0.38, p = 1.63 x 10(-9); multivari
257 Univariate,
multivariate, and time-series analyses were
258 ficantly associated with mortality in either
univariate,
multivariate, or propensity-adjusted analyse
259 Efficacy measures included:
univariate/
multivariate analyses of risk factors influen
260 proposed functional framework in contrast to
univariate or multivariate Random Forest predicting sens
261 I: 0.46-1.34) or microbiological outcomes in
univariate or multivariate regression analyses.
262 such multivariate questionnaire data into a
univariate outcome to represent a surrogate for the late
263 fect will be challenging to detect using the
univariate outcome.
264 DM increased in the post-PAS era (3.4%-3.9%;
univariate P = 0.038), while those for type 1 diabetes m
265 remained statistically stable (47.9%-48.4%;
univariate P = 0.571).
266 sence of adjacent myocardial lesions in both
univariate (
P=0.03) and multivariate analyses ( P=0.049
267 sely associated with medication adherence on
univariate (
P < .0001) and multivariate analysis (P = .0
268 al features that are combined into a single,
univariate pain score.
269 richment scores created from running sums of
univariate phenotype-attribute correlations and phenotyp
270 rval (QTc), female sex, and LQTS genotype as
univariate predictors of symptomatic status.
271 ain Assessment at Withdrawal Speeds), uses a
univariate projection of paw position over time to autom
272 positive likelihood ratios across studies or
univariate random-effects models when bivariate models f
273 sensitivity ca. 30 times larger than for the
univariate reference method.
274 We used a
univariate region of interest analysis, a paired correla
275 We performed
univariate regression analyses to assess the relationshi
276 Moreover,
univariate regression analysis demonstrated that hs-CRP
277 , and beta-blocker use (OR, 3.8, P=0.049) in
univariate regression models.
278 Univariate regression was used to calculate the associat
279 onsistent with results from global tests and
univariate regression.
280 Feature uncertainty predicted
univariate responses in left inferior frontal gyrus, and
281 s was evaluated by aggregating meta-analyzed
univariate results across the 6 continuous electrocardio
282 Whole-brain
univariate results contrasting moving and static sounds
283 rate that associations discovered in routine
univariate screening approaches can be biased by incorre
284 In
univariate sensitivity analysis, clinical benefits of ba
285 A multivariate version of the classical
univariate standard addition method is proposed for the
286 Estimation of the
univariate statistic parameters and genotype plus genoty
287 troscopy and compared using multivariate and
univariate statistical analyses to identify significant
288 discriminatory m/z features was tested using
univariate statistics and tandem MS performed to elucida
289 ificantly longer PFS and OS (both P <= 0.03;
univariate survival analyses) whereas RANO criteria were
290 On
univariate survival analysis, TNM stage (p < 0.01), mGPS
291 iated with BDI not identified using standard
univariate techniques.
292 miRNAs that are not marginally detectable in
univariate testing methods.
293 .01), and rs12415501 (in NEURL, p = 0.03) on
univariate testing.
294 llected variables with PEP was assessed with
Univariate tests and multivariable logistic regression a
295 ulated Fisher-exact p-values for a series of
univariate tests.
296 Univariate time course analyses indicated that intra-epi
297 Univariate time-dependent analyses revealed that isolati
298 negative feedback model to be inferred from
univariate time-series data.
299 Univariate (
UVA) and multivariable Cox regression (MVA)
300 Univariate volume-of-interest analyses demonstrated sign