ライフサイエンスコーパス: categorical variable

1 .002 for interaction with visual acuity as a categorical variable).

2 rion (both analyzing eGFR as a continuous or categorical variable).

3 ixed datatypes (in this study, numerical and categorical variables).

4 ove and below the Leapfrog threshold), and a categorical variable.

5 ip when volume is tested as a dichotomous or categorical variable.

6 HBV viral load was analyzed as a categorical variable.

7 tures while controlling for confounding by a categorical variable.

8 aluated according to BMI as a continuous and categorical variable.

9 G/HDL ratio were analyzed as a continuous or categorical variable.

10 on procedures when there is confounding by a categorical variable.

11 inary (discordant vs concordant) and 4-level categorical variable.

12 es to costs) was modeled as a continuous and categorical variable.

13 t-term UFP concentration as a continuous and categorical variable.

14 er TAPSE/sPAP was modeled as a continuous or categorical variable.

15 xture analyses with effect modification by a categorical variable.

16 The exposure was considered as a categorical variable.

17 e fitted first as a continuous and then as a categorical variable.

18 oor outcome neither as a continuous nor as a categorical variable.

19 erved only when the volume was analyzed as a categorical variable.

20 entration was analyzed as a continuous and a categorical variable.

21 r ordinal variables and chi-square tests for categorical variables.

22 compared with chi2 test for independence of categorical variables.

23 re not distributed normally or when they are categorical variables.

24 sessment of Cancer Therapy-General scores on categorical variables.

25 ontinuous variables and chi-square tests for categorical variables.

26 continuous variables and the chi(2) test for categorical variables.

27 pressed as mean values) and chi(2) tests for categorical variables.

28 r continuous variables and the chi2 test for categorical variables.

29 iables and the chi2 or Fisher exact test for categorical variables.

30 tinuous effect modifiers were represented as categorical variables.

31 ts for continuous variables and x2 tests for categorical variables.

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

33 for continuous variables and proportions for categorical variables.

34 f variance and chi2 tests for continuous and categorical variables.

35 e association between year treated and other categorical variables.

36 the outcomes were analyzed as continuous or categorical variables.

37 tinuous variables and Fisher exact tests for categorical variables.

38 n chi2 comparison of means was performed for categorical variables.

39 e and respiratory distress on examination as categorical variables.

40 ptive statistics and the chi-square test for categorical variables.

41 uous variables and the Fisher exact test for categorical variables.

42 The Fisher exact test was used for categorical variables.

43 The x(2) was used to compare categorical variables.

44 variables and with the chi-squared test for categorical variables.

45 testing with Holm-Bonferroni correction for categorical variables.

46 tion among the 3 vaccines and continuous and categorical variables.

47 es, and the Fisher exact test was applied to categorical variables.

48 d Pearson chi2 test or Fisher exact test for categorical variables.

49 neurological and autonomic manifestations as categorical variables.

50 and the Pearson chi-square test was used for categorical variables.

51 for continuous variables and chi(2) test for categorical variables.

52 ontinuous variables and the McNemar test for categorical variables.

53 continuous variables and the chi(2) test for categorical variables.

54 rmality in brain structure was extracted for categorical variables.

55 oxon rank-sum test for numerical and ordered categorical variables.

56 and either the Fisher exact or chi2 test for categorical variables.

57 ntinuous variables and Fisher exact test for categorical variables.

58 informative than treating the phenotypes as categorical variables.

59 PT of 12 to 14 days (P = .01 [PT analyzed as categorical variable]).

60 was evaluated both as a continuous and as a categorical variable (0-6 hours, 6-12 hours, 12-24 hours

61 s (dependent variable) was defined as a four categorical variable: (1) no victimization or perpetrati

62 To compare categorical variables, a chi-square test was employed, w

63 ation (all p < 0.05) for both continuous and categorical variables across cohorts.

64 was summarized by 10 clinical and laboratory categorical variables (age at onset, large joint involve

65 d mean arterial pressure were used either as categorical variables (age-, race- and sex-specific valu

66 Cross-sectional analyses of quantitative and categorical variables among groups were performed with o

67 Bonferroni corrections were used to compare categorical variables among groups.

68 to two empirical datasets containing largely categorical variables: an anthropological survey of rice

69 ted as the testing of associations between a categorical variable and a continuous variable.

70 h-dimensional variable for each value of the categorical variable and comparing these results by subt

71 el and usual care arms using a chi2 test for categorical variables and a t test for comparisons betwe

72 nificance, chi(2) analysis was performed for categorical variables and a t test or analysis of varian

73 mpared by means of the Fisher exact test for categorical variables and an unpaired t test for continu

74 e Chi-square test or Fisher's exact test for categorical variables and ANOVA or Kruskal-Wallis for co

75 e calculated mean total AARRSI scores across categorical variables and assessed differences between g

76 assessed by logistic regression modeling for categorical variables and by Cox proportional hazards mo

77 However questionnaire data often contains categorical variables and common statistical model assum

78 s and time to hemostasis (TTH), presented as categorical variables and compared with a chi2 test or a

79 curves and a corresponding log-rank test for categorical variables and Cox regression for continuous

80 d into cohorts in relation to the considered categorical variables and data were compared by using th

81 ncy distribution tables with percentages for categorical variables and means and standard deviation o

82 hazard coefficients associated with baseline categorical variables and quintiles of continuous variab

83 fferences were evaluated with the 2 test for categorical variables and Student t test for continuous

84 performed by Pearson's chi-squared test for categorical variables and student's t-test for quantitat

85 Distribution of categorical variables and survival rates across cancer t

86 rral decisions was assessed using chi(2) for categorical variables and t test for continuous variable

87 action were analyzed with the chi 2 test for categorical variables and the Student t test for age and

88 d chi(2) and Fisher's exact tests to compare categorical variables and the t test or the Mann-Whitney

89 of the Pearson chi2 or Fisher exact test for categorical variables and the two-sample t test for cont

90 groups were compared using the chi2 test for categorical variables and the Wilcoxon-Mann-Whitney test

91 , including the difficulties of dealing with categorical variables and triangulating effectively to a

92 using Pearson chi2 or Fisher exact tests for categorical variables and Wilcoxon rank-sum tests for co

93 ipid concentrations (either as continuous or categorical variables) and incident MACEs (N = 6,901; n

94 sessed using contingency table analysis (for categorical variables) and Student's t-tests for (contin

95 as modeled as a continuous variable and as a categorical variable, and its relation with the risk of

96 continuous variables, Fisher exact tests for categorical variables, and generalized estimating equati

97 inuous variables and logistic regression for categorical variables, and interrater and intrarater rel

98 ata, Chi-squared or Fisher's exact tests for categorical variables, and one-way ANOVA with Bonferroni

99 were performed using a Fisher exact test for categorical variables, and t tests or Mann-Whitney tests

100 Fisher's exact test was used to evaluate categorical variables, and the Mann-Whitney test was use

101 The Rao-Scott chi(2) test was used for categorical variables, and the T test was used for conti

102 d to examine unadjusted associations between categorical variables, and Wilcoxon rank-sum test was us

103 Categorical variables are presented as frequencies and p

104 s, were performed to evaluate continuous and categorical variables as applicable.

105 ariables as mean with standard deviation and categorical variables as percentages.

106 sus control) and period (modeled as a weekly categorical variable) as fixed effects with additional a

107 sis and log-rank tests were used to identify categorical variables associated with RD (eGFR <75% of n

108 ic risk score as a continuous variable and a categorical variable based on quartile (quartile 1, quar

109 l number of resected nodes was examined as a categorical variable based on quartiles (category 1: < o

110 he translation of a continuous variable to a categorical variable based on the perception of the exam

111 STE after intervention (MaxSTPost); and 5) a categorical variable based upon MaxSTPost (High Risk).

112 owed by multivariable regression models with categorical variables based on quartiles of the distribu

113 The distribution of categorical variables between groups was analyzed by usi

114 xact test was used to compare differences in categorical variables between groups.

115 med Fisher exact test or chi-square test for categorical variables between the cohort that did and di

116 lism has been routinely operationalized as a categorical variable (bilingual/monolingual), whereas it

117 istics were used to summarize continuous and categorical variables by mutation.

118 step, where K is the number of values hidden categorical variables can take.

119 el of individual hospitals by using TTA as a categorical variable comparing outcomes between late and

120 nal markers, modeled as either continuous or categorical variables, correlated with FMD.

121 Impact of D-MELD as a continuous and categorical variable (D-MELD 0-4, 5-10, >10) on early, 3

122 olic from baseline to 6 months(assessed as a categorical variable) decrease or increase of >2 mm Hg c

123 large datasets using thousands of different categorical variable descriptors, as well as various met

124 d Parkinson's disease age of onset both as a categorical variable (dichotomised by median onset) and

125 ere studied using design of experiments with categorical variables (extraction buffers, cleanup sorbe

126 for continuous outcomes and proportions for categorical variables. Fifty-four women were enrolled an

127 ys was performed with chi-square testing for categorical variables (Fisher's exact test used for viol

128 ) 0.84 [95% CI 0.73-0.96], p=0.012) and as a categorical variable for low versus high density (aHR 1.

129 DOPBP was analyzed as a categorical variable grouped as high (>90 mm Hg; n=40),

130 The best predictive model had four categorical variables: hemodynamic support (ECMO, ventil

131 Using CTS5 score as a categorical variable, HER2- patients with high-risk leve

132 In multivariable models, as a categorical variable, high C-index (>1.34) was the only

133 , noise) were compared by using t tests, and categorical variables (image quality) were compared by u

134 riable in Poisson regression models and as a categorical variable in multinomial logistic regression

135 Descriptive statistics were used to analyze categorical variables in terms of size and proportions.

136 e case of age or body mass index (BMI)-or as categorical variables in the case of sex and alcohol con

137 the final risk-assessment model contained 10 categorical variables including congestive heart failure

138 analysis was performed using chi2 tests for categorical variables; independent t tests for continuou

139 ys of PPS prescriptions filled and created a categorical variable indicating total exposure.

140 owledge gap remains for the incorporation of categorical variables into these advanced method optimiz

141 When assessed as a categorical variable, LNR was the most powerful manner t

142 tivariable analysis, PI examined either as a categorical variable, low versus high PI (hazard ratio,

143 A1c levels were examined as a continuous and categorical variable (<5.7%, 5.7%-6.5%, and >6.5%).

144 nsferring ED) as a continuous variable and a categorical variable (<=120 minutes, >120 minutes).

145 le (DTN) time as a continuous variable and a categorical variable (<=60 vs >60 minutes).

146 of RS% was assessed both as a continuous and categorical variable: < 5% (n = 56), 5%-14% (n = 32), 15

147 son chi-square test or Fisher exact test for categorical variables, Mann-Whitney U test for continuou

148 Proportions were analyzed for categorical variables; means and SDs were analyzed for c

149 Drug exposure was modelled primarily as a categorical variable (n = 23 studies).

150 trength of state moratorium protections as a categorical variable: none, weak (blocking court hearing

151 rs) was evaluated as both a continuous and a categorical variable (normal defined as <25.0; overweigh

152 uated both as a continuous variable and as a categorical variable (normal, 18.5 to 24.9; overweight,

153 The impact of QRS duration, evaluated as a categorical variable of <85 ms versus 85 to 99 ms and >/

154 MELD-Na score was treated as a categorical variable of scores <36, 36-40, and >40.

155 HI-5 score of less than or equal to 3) and a categorical variable of symptom severity on the MHI-5.

156 isclassification (i.e., measurement error of categorical variables) of predictors on random-forest mo

157 Existing methods either treat HLA as a categorical variable or represent an HLA by its alphanum

158 overweight, and 3 subgroups of obesity) as a categorical variable or transformations, including fract

159 e chi-square test or Fisher's exact test for categorical variables or the t test or Kruskal-Wallis te

160 was performed with the Fisher exact test for categorical variables or the Wilcoxon rank-sum test for

161 ere compared by chi(2) or Fisher exact test (categorical variables) or Wilcoxon rank-sum (continuous

162 us variables, chi2 or Fisher exact tests for categorical variables, or Fisher exact test alone when e

163 [95% CI, 0.99-1.01]) or when considered as a categorical variable (patients ordered by elapsed time a

164 When treated as a categorical variable, patients with the maximum h-ESAS s

165 r or area-under-the-curve for continuous and categorical variables, respectively, provides comparativ

166 and chi-square tests compared continuous and categorical variables, respectively, while multivariate

167 act test were used to compare continuous and categorical variables, respectively.

168 ests and chi-square tests for continuous and categorical variables, respectively.

169 a, with recent drought classified as ordinal categorical variable (severe: <=10th percentile; mild/mo

170 1.099 (1.038-1.164), p < 0.0012) as well as categorical variable splitting data at the median value

171 son's chi-squared or Fisher's exact test for categorical variables, Student's t-test, and Wilcoxon ra

172 imensional variable, such as an image, and a categorical variable, such as the presence or absence of

173 predictor of baseline damage, measured as a categorical variable (t-test = 2.357, beta-standardized

174 Fisher exact tests for categorical variables, t test for continuous variables,

175 A cases using Pearson's chi-square tests for categorical variables, t tests for continuous variables,

176 Categorical variable that indexed the degree of cannabis

177 When arterial stiffness was analyzed as a categorical variable, the highest quartiles of aPWV (HR,

178 When CAPS (T(max) > 6 s) was treated as a categorical variable, the interaction remained significa

179 obal Assessment Scale [GAS] scores) and as a categorical variable, the percentage of maintenance eval

180 When treating the INR as a categorical variable, the risk of a composite bleeding e

181 When treating the INR as a categorical variable, the risk of composite thromboembol

182 For categorical variables, the sensitivity and specificity o

183 The chi-squared test was used for categorical variables, the student's t-test for continuo

184 sher exact test were used for comparisons of categorical variables; the Kruskal-Wallis test and Mann-

185 Family history score can also be used as a categorical variable to stratify families.

186 which users can include both continuous and categorical variables to achieve objectives specific to

187 and multivariable models for continuous and categorical variables to assess the relation of selected

188 th HLA mismatches as continuous variable, as categorical variable (total number of HLA mismatches), a

189 We compared categorical variables using Fisher exact test and contin

190 earson correlation coefficients and compared categorical variables using the Fisher exact test.

191 non-parametric Kruskal-Wallis test, and for categorical variables using the Pearson x(2) test.

192 For general obesity, a categorical variable was created: 1) eutrophic/lost weig

193 nostic scoring rule (ProVent 14 Score) using categorical variables was created in the development coh

194 Categorical variables were analyzed by proportional diff

195 Categorical variables were analyzed by the chi(2) test a

196 All categorical variables were analyzed using chi2 or Fische

197 ons with longitudinal change in cytokines as categorical variables were analyzed using multivariable

198 Categorical variables were analyzed using Pearson chi-sq

199 Dichotomous and categorical variables were analyzed using Pearson chi-sq

200 Categorical variables were analyzed using Pearson's chi-

201 us variables were analyzed using t test, and categorical variables were analyzed using x2.

202 sed to analyze continuous variables, whereas categorical variables were analyzed via Chi-square or Fi

203 Categorical variables were analyzed with Pearson chi(2)

204 Differences in categorical variables were assessed using the chi(2) tes

205 Defined continuous and categorical variables were collected on consecutive pati

206 Categorical variables were compared between patients wit

207 Categorical variables were compared by chi(2) test and c

208 median [first quartile-third quartile]), and categorical variables were compared by Fisher exact test

209 Categorical variables were compared by using the exact c

210 Categorical variables were compared using chi-square/Fis

211 Categorical variables were compared using the chi(2) tes

212 erformed using independent-sample t-test and categorical variables were compared using the chi-square

213 Categorical variables were compared using the chi-square

214 Categorical variables were compared using the chi2 test,

215 Categorical variables were compared using the Pearson ch

216 ompared using an independent-samples t test; categorical variables were compared using the Pearson ch

217 Numerical and categorical variables were compared using the Wilcoxon r

218 ables were compared with Student t test, and categorical variables were compared with the Fisher exac

219 Categorical variables were evaluated by using the Fisher

220 Differences in categorical variables were examined by using Pearson chi

221 Differences in categorical variables were measured by using the Fisher

222 Location and SUV(max) categorical variables were predictive of IBL interpretat

223 iables dichotomized using the top 2 options; categorical variables were recoded into binary variables

224 adjusted incidence rate ratios of these nine categorical variables were scaled and summed to create t

225 Categorical variables were summarized as relative risk a

226 Categorical variables were summarized using frequencies

227 Categorical variables were summarized using proportion a

228 Descriptive and categorical variables were summarized with counts and pe

229 ormally distributed, and Chi-square test for categorical variables were used in univariable compariso

230 tinuous variables and contingency tables for categorical variables were used.

231 ase prediction algorithm was developed using categorical variables, which allows physicians to predic

232 However, BO with mixed numerical and categorical variables, which is of particular interest i

233 proach that incorporates both continuous and categorical variables while also utilizing a multivariat

234 ECMO was explored both as a continuous and a categorical variable with Cox proportional hazard models

235 -sample t-test or Mann-Whitney test, whereas categorical variables with Chi-squared or Fisher exact t

236 Drug exposure was primarily modelled as a categorical variable, with insulin associated with impro