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

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

5 The exposure was considered as a categorical variable.

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

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

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

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

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

11 neurological and autonomic manifestations as categorical variables.

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

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

14 ontinuous variables and the McNemar test for categorical variables.

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

16 rmality in brain structure was extracted for categorical variables.

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

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

19 informative than treating the phenotypes as categorical variables.

20 compared with chi2 test for independence of categorical variables.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

36 Distribution of categorical variables and survival rates across cancer t

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

71 [95% CI, 0.99-1.01]) or when considered as a categorical variable (patients ordered by elapsed time a

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

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

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

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

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

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

78 For categorical variables, the sensitivity and specificity o

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

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

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

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

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

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

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

86 Categorical variables were analyzed with Pearson chi(2)

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

88 Defined continuous and categorical variables were collected on consecutive pati

89 Categorical variables were compared by using the exact c

90 Categorical variables were compared using chi-square/Fis

91 Categorical variables were compared using the chi-square

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

93 Categorical variables were evaluated by using the Fisher

94 Differences in categorical variables were examined by using Pearson chi

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

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

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

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