ライフサイエンスコーパス: probit

1 emonstrate its application in a large trial (PROBIT).

2 The probit 9 standard for quarantine treatment efficacy has

3 probability was 0.28 FFU/ml as determined by probit analysis (p </= 0.05).

4 Although probit analysis could not be performed with the availabl

5 Probit analysis determined the 95% detection level was 5

6 potential control failure was detected using probit analysis estimates for cypermethrin, deltamethrin

7 Thresholds were determined based on probit analysis of psychometric functions generated usin

8 lds (FAVL-ED50) were also determined using a probit analysis of the dosage.

9 Probit analysis results revealed that PS externalization

10 still protect 50% of mice was calculated by probit analysis to be 9.4 hours.

11 e limit of detection (LOD), as determined by probit analysis using dilutions of the 2nd HBV internati

12 The limit of detection calculated by probit analysis was 23.8 copies/ml using the 2nd Interna

13 Analytical sensitivity determined by probit analysis was between 6.2 and 9.0 IU/ml.

14 The analytical sensitivities determined by probit analysis were 19.3 copies/ml for the 1-ml assay a

15 c regression produces similar results to the probit analysis.

16 ary responses and ED50s were estimated using Probit analysis.

17 d was determined to be 7.74 HCV RNA IU/ml by probit analysis.

18 ile ranges (IQR, 25%-75% seen) determined by probit analysis.

19 ure threshold for damage was calculated with probit analysis.

20 a sets for HP and TNAI were insufficient for probit analysis; however, there was 100% detection at >/

21 outcome were recorded and analyzed with both probit and logistic regression analyses.

22 Mortality data from previously reported probit and logit analyses from thousands of patients tre

23 ed an inverse probability-weighted two-part, probit, and generalized linear model to estimate increme

24 e, partially mediated by positive symptoms) (probit coefficient [beta] = 0.12; P = .002); while stabl

25 increases in the probability of tooth loss (probit coefficients were 0.469 (95% confidence interval:

26 The bivariate probit demonstrated significant correlation between the

27 The mean and SD of the probit fitted cumulative Normal function were used to es

28 onmental factors on the basis of the ordinal probit model (also called threshold model) that assumes

29 A bivariate probit model estimated the effects of risk while control

30 The probit model indicated that outcome improved across the

31 A quasi-experimental instrumental variables probit model of the association correlation of ECT admin

32 Comparison of probit model results with previous results demonstrates

33 The probit model suggested that increasing age (p=0.03), pae

34 between the 2 groups, we created a bivariate probit model to estimate the probability of repeat inter

35 A dynamic random effects bivariate panel probit model with initial conditions (Wooldridge-type es

36 A dynamic version of a random effects panel probit model with initial conditions is estimated on the

37 We estimated a probit model with state indicators to adjust for state-l

38 The proposed ordinal probit model, combined with the composite model space fr

39 rger than those of the instrumental variable probit model.

40 oth loss by fitting an instrumental variable probit model.

41 intrinsic conditional autoregressive spatial probit models were used to determine the risk of a child

42 Multivariable ordinary least squares and probit models were used to estimate the association betw

43 We used an ordered probit multivariate analysis to link evaluation scores t

44 We analysed paired comparison data using probit regression analysis and rescaled results to disab

45 We analysed paired comparison responses with probit regression analysis on all 220 unique states in t

46 By applying probit regression analysis, the analytical sensitivity w

47 variate' representation of the cluster, in a probit regression model.

48 We then used linear or probit regression to estimate the associations of the po

49 We first used probit regression to model the associations of 2 tobacco

50 ivariable logistic and instrumental variable probit regressions on data from the Multiple Risk Factor

51 We developed an ordered probit statistical model to assess adjusted outcome as a

52 Methods considered include probit structural equation models, 2-stage logistic mode

53 whole blood standards (validation); and ii) PROBIT trial samples (application) in which paediatricia

54 omotion of Breastfeeding Intervention Trial (PROBIT), we included 13,557 participants (79.5% response

55 In PROBIT, we successfully quantified fasting adiponectin f