ライフサイエンスコーパス: chi-square test

1 5, 95% confidence interval 0.2-0.9, p=0.025, Chi squared test)).

2 jects but not in any Caucasians (P = 0.0005, chi square test).

3 istical significant difference (p < <.001 at Chi square test).

4 onventional-ventilation group (P=0.85 by the chi-square test).

5 ons (53.0% vs 35.4%, respectively; P<0.0001, chi-square test).

6 ile were the same (p=0.007, likelihood ratio chi-square test).

7 nger counterparts (p<0.001, likelihood ratio chi-square test).

8 e points; 95% CI, -3.3 to 2.8; P=0.88 by the chi-square test).

9 e points; 95% CI, -3.0 to 6.7; P=0.45 by the chi-square test).

10 ce interval [CI], -4.0 to 5.6; P=0.75 by the chi-square test).

11 ezetimibe group (1% vs. 5%, P = 0.04 by the chi-square test).

12 anti-CCP antibody-negative RA (P = 0.01, by chi-square test).

13 ees (26.8%) showed an increase (P < 0.001 by chi-square test).

14 gns was found to be significant (P < 0.0001, chi-square test).

15 can and 11% of Hispanic students (P = 0.001, chi-square test).

16 harbored predominantly serotype c (P = 0.05, chi-square test).

17 only 4% of tTA/TAg/ER-alpha mice (P = 0.014, chi-square test).

18 or DOR1 mRNA (555/651 vs. 132/138, P > 0.3, chi-square test).

19 than that expressing MOR1 mRNA (P < 0.0001, chi-square test).

20 ion (80% and 62.5%, respectively; p = 0.004, chi-square test).

21 e superior (rated as "excellent") (P < 0.05, chi-square test).

22 (18%) of 50 in the control group (p < 0.001, chi-square test).

23 roved with the use of the DSpecs (P = 0.024, chi-square test).

24 respectively (9% vs 1.5% vs 0.2%; P < .001, chi-square test).

25 symptoms develop (50.0% vs. 9.6%; P < 0.001, chi-square test).

26 teral obstruction (16.9% vs 10.2%, p < 0.001 Chi-square test).

27 nd Comp groups were significant (P < 0.0001, chi-square test).

28 hen compared to those of controls (p < 0.05, chi-squared test).

29 All comparisons were analyzed by chi square test.

30 with 1-way analysis of variance (ANOVA) and chi-square test.

31 Dosing methods were compared using McNemar's chi-square test.

32 y with sepsis volume level were evaluated by chi-square test.

33 cate significant crossover interference in a chi-square test.

34 by using the c statistic and Hosmer-Lemeshow chi-square test.

35 yzed using Fisher's exact test and Pearson's chi-square test.

36 ar regression, Wilcoxon's rank sum test, and chi-square test.

37 data was analyzed using the Fisher exact or chi-square test.

38 ties were compared using a two-way ANOVA and Chi-square test.

39 Analyses: Wilcoxon-paired test, Chi-square test.

40 orical variables were analyzed using Pearson chi-square test.

41 ategorical variables were compared using the chi-square test.

42 ups were examined by Mann-Whitney U test and chi-square test.

43 ated measures analyses, and the CGI-I with a chi-square test.

44 physical activity was assessed by using the Chi-square test.

45 were analyzed by descriptive statistics and chi-square test.

46 st, Mann-Whitney U test, or likelihood ratio chi-square test.

47 yocardial infarction and were analyzed using chi square tests.

48 en cases and controls was conducted by using chi-square tests.

49 cross sodium levels using Kruskal-Wallis and chi-square tests.

50 valence was compared across FRS strata using chi-square tests.

51 lyzed using Cochran-Mantel-Haenszel tests or chi-square tests.

52 nonparticipants were examined by t-tests and chi-square tests.

53 Analyses included descriptive statistics and chi-square tests.

54 esults were compared using Fisher's exact or chi-square tests.

55 ferences in accuracy by clinician type using chi-square tests.

56 e expected ratio of 1:2:1 by goodness-of-fit chi-square tests.

57 terventions in each group were analyzed with chi-square tests.

58 sus region, and place of care using adjusted Chi-square tests.

59 Statistical comparisons are made using chi-square tests.

60 e cases were compared by using the Tukey and Chi-Square Tests.

61 awareness among clinicians were assessed by chi-square tests.

62 etween antibiotic prescription cohorts using chi-square tests.

63 We assessed for associations using chi-square tests.

64 f the expected and observed frequencies used Chi-squared tests.

65 pected and observed frequency of gender used Chi-squared tests.

66 cy arm were analyzed using cluster-corrected Chi-squared tests.

67 using the one-way ANOVA, Kruskal-Wallis and chi-squared tests.

68 ical variables were analyzed using Pearson's chi-squared tests.

69 parent McKrae (6.1 versus 11.8%; P = 0.0025 [chi-square test]).

70 peptide (univariate and multivariable model chi-square test: 105.0 and 48.4; both p < 0.0001) and se

71 nts (area under the curve 0.66 for BNP only [chi-square test = 12.9, p = 0.0003], and 0.70 for BNP pl

72 ility provided significant additional value (chi-square test = 13.1, p = 0.004) to baseline predictor

73 2.9, p = 0.0003], and 0.70 for BNP plus MPO [chi-square test = 15.87, p = 0.0004]).

74 York Heart Association functional class IV (chi-square test: 18.8 and 9.6; p < 0.0001 and p = 0.0020

75 ving less interventricular mechanical delay (chi-square test: 29.8 and 8.8; p < 0.0001 and p = 0.0029

76 ase as the cause of ventricular dysfunction (chi-square test: 34.9 and 7.4; p < 0.0001 and p = 0.0066

77 the FBF group, and 85.7% in the SF-M group (chi-square test = 4.13, P = 0.02; one-tailed test with t

78 .0001) and severity of mitral regurgitation (chi-square test: 44.0 and 17.9; both p < 0.0001) at 3 mo

79 In a Cox proportional hazards model (chi-square test = 89.4) adjusting for baseline character

80 causality, we present an adapted functional chi-squared test (AdpFunChisq) that rewards functional p

81 with high significance (P < 0.0001, Pearson chi-square test) an embryonically lethal phenotype of ho

82 Chi-square tests, ANCOVA, and multiple regression analys

83 group with similar injury grade (p < 0.005, chi square test and Student's t test).

84 ion among certified nursing assistants using chi square tests and binomial logistic regression models

85 Chi square tests and logistic regressions were used to t

86 Chi squared tests and Wilcoxon rank-sum were used to com

87 Data were analyzed using the Chi-square test and analysis of variance.

88 TX efficacy or MTX toxicity according to the Chi-square test and binary logistic regression.

89 ditional association methods such as Pearson chi-square test and Fisher Exact test are single test me

90 Descriptive statistics, chi-square test and Fisher's exact test were used for da

91 Statistical analysis for rejection used the chi-square test and for graft survival used the log-rank

92 We used the chi-square test and I to assess for statistical heteroge

93 hospitalization endpoints were tested using chi-square test and incidence rate ratio (IRR) estimatio

94 Chi-square test and logistic regression analysis were co

95 s and analysed using descriptive statistics, chi-square test and logistic regression models.

96 ng the Mantel-Haenszel correlation statistic chi-square test and logistic regression.

97 Statistical analyses performed included the chi-square test and multivariate regression analysis.

98 ographic and other details were tested using Chi-square test and other tests, and a p-value of < 0.05

99 Data were analyzed with unpaired t-tests, Chi-square test and Receiver Operating Characteristic (R

100 Chi-square test and stepwise logistic regression were em

101 istinguished NSAID treatment from placebo by chi-square test and that had a placebo response rate of

102 ional logistic regression analysis using the chi-square test and the Cox proportional hazards model.

103 0-44 and 45-59).The data were analyzed using Chi-square test and the significance level was set as p<

104 Chi-square testing and regression analysis were performe

105 Chi-square tests and a log-binomial multivariable model

106 Chi-square tests and cox-regression was used to determin

107 Chi-square tests and Fisher's exact tests were used to c

108 onal psychotherapy were compared by means of chi-square tests and life table and random effects model

109 italopram and placebo were compared by using chi-square tests and linear modeling.

110 Chi-square tests and logistic regression analyses were u

111 Results were analyzed using chi-square tests and logistic regression analysis.

112 Chi-square tests and multilevel logistic regression anal

113 ogical characteristics of the patients using chi-square tests and multivariate logistic regression an

114 tellite polymorphisms was investigated using chi-square tests and multivariate logistic regression an

115 ared response rates by treatment group using chi-square tests and multivariate logistic regression mo

116 s and patient perception were analyzed using Chi-square tests and Spearman's rank correlation.

117 and genotype frequencies were analyzed using chi-square tests and stepwise logistic regression.

118 Data entry and analysis were performed using chi-square tests and the Statistical Package for Social

119 of descriptive data were analyzed using the chi-squared test and Mann-Whitney U-test.

120 providers were compared across groups using chi-squared tests and analysis of variance.

121 Chi-squared tests and conditional logistic regression mo

122 V) analyses were performed using the Pearson Chi-squared tests and Cox proportional hazard, respectiv

123 Chi-squared tests and Generalized Estimating Equations w

124 tabulated and analyzed with students' t and chi-squared tests and logistic regression.

125 Chi-squared tests and multivariable logistic regression

126 Chi-squared tests and multivariate Cox regression analys

127 Chi-squared tests and regression analysis for clustered

128 1; P = 0.0303, OR = 3.45, 95% CI 1.05-11.35, chi-square test) and three HLA alleles (DQB1*06:01, DQA1

129 CpG island methylator phenotype (p = 0.036, Chi square test), and resistant cell lines harbored meth

130 Descriptive statistics, Pearson chi-square test, and analysis of variance were used for

131 hree statistical tests (Pearson correlation, Chi-square test, and ANOVA) to assess the differences in

132 cluded analysis of variance, Mantel-Haenszel chi-square test, and logistic regression.

133 re analyzed by using descriptive statistics, Chi-square test, and multivariate logistic regression.

134 sing a 1-way analysis of variance, Pearson's chi-square test, and simple linear regression.

135 Descriptive analysis was performed with chi-square testing, and risk factors for EE were identif

136 treatment thresholds were then assessed via chi-square tests, and associations between the decision

137 E program were tested with 2-sample t tests, chi-square tests, and Fisher exact tests.

138 nopause were determined by Student's t test, chi-square tests, and Fisher's exact test.

139 onse was analyzed using Pearson correlation, chi-square tests, and logistic regression.

140 nts with sepsis were compared using t tests, chi-square tests, and logistic regression; p values less

141 Analysis of variance, chi-square tests, and proportional hazards models were u

142 Cross-tabulations, chi-squared tests, and Fisher's exact tests were used to

143 Descriptive statistics, chi-square tests, ANOVA, and bivariate logistic regressi

144 ce of each component based on a conventional chi-squared test approach.

145 ociation with the PTPN22 SNP was analyzed by chi-square test as implemented in Stata software.

146 orical variables were analyzed using Pearson chi-square tests as well as covariate-adjusted Cochran-M

147 than 20 mmHg at CRVO presentation (P = 0.02, Chi-square test) as well as in the ischemic CRVO group c

148 isk, and analyzed using Mann Whitney U test, Chi-square test, as appropriate, a P-value <=0.05 was co

149 cidence of death within 24 h was compared by chi-square test between Definity and unenhanced procedur

150 re were no significant associations (P>0.05, chi-square test) between catheter type, side of catheter

151 There was an association (P=0.04, chi-square test) between infusion type and positive find

152 ums compared MIC distributions by unit type; chi-square tests compared agents and antibiotic classes.

153 yzed using SPSS v22; independent t-tests and chi-square tests compared continuous and categorical var

154 gorical measures were compared using Pearson chi-square tests; continuous measures were compared usin

155 Descriptive statistics, chi-square tests, correlations, and regression analyses

156 rson's correlation test, Wilcoxon rank test, Chi-square test, Cox regression, and Kaplan-Meier analys

157 Chi-square test, cross tabulation, and ROC curves were u

158 Chi-square tests evaluated categoric outcomes and Poisso

159 as A, B, C, or D and were compared using the chi-square test, Fisher exact test, analysis of variance

160 fferences between groups were performed with chi-square test, Fisher exact test, and t tests.

161 Descriptive, Chi-square test, Fisher's exact test, one way ANOVA, and

162 Basic descriptive statistics, chi-square test, Fisher's exact test, Pearson correlatio

163 Statistical analysis, with Pearson chi-square tests, Fisher exact test, and multiple logist

164 Chi-square tests, Fisher exact tests, and multivariate l

165 AC for each micronutrient tertile by using a chi-square test for binary variables and analysis of var

166 ntal finding, performed Fisher exact test or chi-square test for categorical variables between the co

167 nk sum test for nonnormally distributed, and Chi-square test for categorical variables were used in u

168 Change over time was tested using the chi-square test for categorical, Wilcoxon test for non-p

169 aracteristic curve = 0.934) and calibration (chi-square test for goodness-of-fit = 9.31, p = 0.317) o

170 endophthalmitis per vitreous substitute via chi-square test for independence.

171 A simple, better chi-square test for interference in two-factor crosses i

172 out proximal disease were compared using the chi-square test for ordinal variables and Student's t-te

173 blished previously (prediction group) by the chi-square test for proportions.

174 reliable statistical inference of Pearson's chi-square test for the [Formula: see text] contingency

175 Based on the calibration chi-square test for the medication group, the OHTS calcu

176 re 8%, 12% and 20%, respectively (two-tailed chi-square test for trend 5.61, p = 0.02, OR 0.34 for co

177 Chi-square test for trend was used to detect changes in

178 exposure to secondhand smoke (P<0.001 by the chi-square test for trend) that was confirmed by a decre

179 4, 16% in 2005, and 21% in 2006 (P < 0.0001, chi-square test for trend).

180 004, 2005, and 2006, respectively (P = 0.04, chi-square test for trend).

181 1998 and to 0.5 percent in 1999 (P<0.001 by chi-square test for trend).

182 did those receiving placebo (P = .04 by the chi-square test for trend).

183 resuscitation events over time evaluated by chi-square test for trend.

184 components and the severity of RE using the chi-square test for trend.

185 increased significantly with age (P = 0.001 [chi-square test for trend]) in women with a family histo

186 mple t test to compare continuous variables, chi-square testing for categorical comparisons, and the

187 ceiving A2 or A2B kidneys was performed with chi-square testing for categorical variables (Fisher's e

188 stical software SPSS version 26 and employed Chi-square tests for analysis.

189 Chi-square tests for association allowed the identificat

190 en male and female SCA cases using Pearson's chi-square tests for categorical variables, t tests for

191 ests for continuous or ordinal variables and chi-square tests for categorical variables.

192 udent's t tests for continuous variables and chi-square tests for categorical variables.

193 tests for continuous variables and Pearson's chi-square tests for categorical variables.

194 =717) income were compared using t tests and chi-square tests for continuous and categorical variable

195 ntable hospital readmissions using McNemar's chi-square tests for paired data.

196 ges sweetened with LCSs were tested by using chi-square tests for trend and F tests.

197 istical analyses were performed by Pearson's chi-squared test for categorical variables and student's

198 betes risks (Hosmer-Lemeshow goodness-of-fit chi-squared test for each model: P < 0.001).

199 etes induced a significant shift (P < 0.001, chi-squared test for trend) towards increased neuronal c

200 ired Student t tests for continuous data and chi-squared tests for categorical data.

201 analyzed using two-factor ANOVA for age and chi-squared tests for race, ethnicity, and sex.

202 first describe the flaws of the traditional (chi-squared) tests for both allelic and genotypic homoge

203 up was assessed overall and compared by arm (chi squared tests) for those screening positive for glau

204 (P > 0.38 by Cox proportional hazards and by chi-square test) in the 66 high-dose patients (8 develop

205 Chi-square test, independent t test and Spearman's rho c

206 Statistical analysis included chi-square tests, Kaplan-Meier survival curves, and Cox

207 es for creation of prediction tools included chi-square tests, logistic regression models and the lea

208 Chi-square tests, logistic regression, and ordinal regre

209 rigin) and nontransmitted alleles (using the chi-square test of heterogeneity).

210 more powerful in simulations than either the chi-square test of independence or the Kolmogorov-Smirno

211 compared via independent samples t tests and chi-square tests of factor scores, syndrome scores, and

212 Chi-square tests of independence examined differences in

213 Multilevel predictors were assessed through chi-square tests on the respective deviance reductions.

214 Data were analyzed using Pearson chi-square test or Fisher exact test for categorical var

215 ategorical variables were compared using the chi-square test or Fisher exact test.

216 ere determined, and comparisons were made by chi-square test or t-test.

217 les between groups was analyzed by using the chi-square test or the Fisher's exact test, and p < .05

218 ll as perception of risk were analysed using Chi-square test or Univariate Fisher's exact test.

219 Comparisons were made using Pearson chi-square tests or Fisher exact tests for categorical f

220 Bivariate (chi-square tests or the Fisher's exact test) and multiva

221 ither MOR1 mRNA (202/497 vs. 44/86, P > 0.2, chi-square test) or DOR1 mRNA (555/651 vs. 132/138, P >

222 Chi-square tests, ORs, and mixed-effects models were use

223 in comparison to chromosome analysis (8.0%, chi-square test p = 0.000751).

224 hazard ratio (HR), 0.34; 95% CI, 0.13-0.89; chi-square test P = 0.027).

225 86; 95% confidence interval (CI), 0.75-0.98; chi-square test P value = 0.025).

226 In the case-control analyses, Chi-square test P-value was 6.80e-12 and the P-value was

227 substitute and endophthalmitis incidence via chi-square testing (P < 0.0001) was found.

228 and 7.4%, respectively) than in adult (2.6%; chi-square test, P < 0.0001) patients.

229 as 91.0%, with significantly lower accuracy (chi-square test, P < 0.0001).

230 across studies in each resistance category (chi-squared test, p<0.00001, I(2) varied from 95% to 100

231 women of African ancestry (P = 0.002 by the chi-square test; P = 0.006 by Fisher's exact test; and a

232 4% of eyes with PKP, and 8% of control eyes (chi-square test; P = 0.01).

233 s, 76% of PKP eyes, and 80% of control eyes (chi-square test; P = 0.41).

234 Sample proportions were compared by chi square test, quantitative variables with Student t t

235 A chi-square test rejects the null hypothesis that membran

236 itative data was done by unpaired t-test and Chi-Square test, respectively.

237 rs were assessed using Wilcoxon rank sum and chi-square tests, respectively.

238 for cervical LCR or culture; Mantel-Haenszel chi-square test result, 8.58; P = 0.003).

239 A chi-square test revealed that the COI, health and enviro

240 The results of chi-square test revealed that the radiomics feature clus

241 Chi-squared tests revealed significant differences by se

242 In PKU patients, the Chi-Square test showed a significant association between

243 A chi-square test showed fewer positive reactions for DBS

244 Although, chi-square test showed that more players were born in fi

245 Chi-square tests showed statistically significant differ

246 ng Student's t-test, Mann-Whitney U test, or chi-square test (significance, p < .05).

247 95]%, 'Scrambled' = 59 [42 to 95]%; Friedman Chi-squared test statistic 6.5, p = 0.04; visit 2 median

248 00]%, 'Scrambled' = 28 [13 to 63]%; Friedman Chi-squared test statistic 8.4, p= 0.02).

249 Chi-square test, Student's t test, and Cox regression we

250 Data analysis included Fisher's exact test, chi-square test, Student's t-test, analysis of variance,

251 The chi-square test, Student's t-test, and Mann-Whitney U-te

252 Statistical analysis was performed using chi-square test, t test, and analysis of variance.

253 Subsequent statistical analyses involved chi-square test, t test, and logistic regression modelin

254 Chi-square tests, t tests, and multiple regression were

255 Data were analyzed using chi-square tests, t tests, Wilcoxon rank-sum tests, Spea

256 With chi-square tests, the distribution of terminal digit for

257 Bivariate analysis was conducted using the chi-square test to assess associations between hypertens

258 We used the chi-square test to determine whether any of the studied

259 ariate analysis was conducted using weighted chi-square tests to examine associations between hyperte

260 We used the Wilcoxon rank-sum and Pearson chi-square tests to examine race differences in the base

261 We used Wilcoxon rank-sum and Pearson chi-square tests to examine race differences in the base

262 red before and after the policy change using chi-squared tests to identify potentially confounding co

263 for children with NI with a Mantel-Haenszel chi-square test using all 4 y of data combined.

264 xperienced greater mortality rates (p =.001, chi-square test using Fisher's exact method) and increas

265 A chi square test was used for statistical analysis.

266 Chi square testing was used to compare BASDAI scores bet

267 for all continuous variables and the Pearson chi-square test was used for categorical variables.

268 Chi-square test was used for statistic analysis between

269 survival and surgeon experience, the Pearson chi-square test was used to compare visual acuities, and

270 ffected sibling was available, the unmatched chi-square test was used to determine if a meiotic segre

271 determine frequency and percentage, and the chi-square test was used to identify any associations.

272 In the Correlation step, a Chi-square test was used to select potential prognostic

273 Chi-square testing was performed to compare responses by

274 Chi-squared test was conducted to discover which treatme

275 Chi-squared test was used to analyze the association bet

276 A chi-squared test was used to assess statistical signific

277 re expressed as numbers with proportions and Chi-squared test was used to compare proportions.

278 The other significant factor (by chi-square test) was the presence of the shared epitope

279 Here, using a 2x3 chi-square test, we describe a relationship between geno

280 Chi square tests were carried out to test the associatio

281 vity C-reactive protein).Unpaired t-test and Chi-Square test were used to analyze quantitative data a

282 Descriptive statistics and Chi-square test were used to present the proportion of v

283 tistics were used to summarize findings, and chi-square tests were applied to explore associations be

284 Mann-Whitney and Chi-square tests were conducted to evaluate significant

285 tistics, proportions, odds ratios (ORs), and chi-square tests were reported and compared with 2021 US

286 One-way analysis of variance and chi-square tests were used for statistical analysis.

287 The Kruskal-Wallis and chi-square tests were used to analyze baseline differenc

288 Chi-square tests were used to assess differences and tem

289 atistics, odds ratios (ORs), and multinomial chi-square tests were used to assess trends in reporting

290 ANCOVA and Chi-square tests were used to compare the differences be

291 T-tests and chi-square tests were used to determine if there were di

292 Chi-square tests were used to evaluate difference in per

293 Chi-square tests were used to examine differences from p

294 Chi-squared tests were used to evaluate differences betw

295 3% of cases and 7.2% of controls; P = 0.044, chi-square test) were more common in cases than in contr

296 ful strabismus surgery were analyzed using a chi-square test with an alpha of 0.05.

297 introduced for continuous data: a continuous chi-square test with test statistic T(CCS) and a test ba

298 Chi-square tests with Bonferroni-adjusted z-tests were u

299 in rates of key metrics were analyzed using chi-square tests with pairwise z -tests.

300 at the simple association method such as the chi-square test yields a large number of false positives