ライフサイエンスコーパス: regression line

1 surements and increasing the accuracy of the regression line.

2 ith the human LP-pulvinar value close to the regression line.

3 masses, phosphopeptides tend to fall off the regression line.

4 of voxel mu-OR binding values around the age regression line.

5 uncorrelated with the slope of the power law regression line.

6 l control subjects generally agreed with the regression lines.

7 was significantly associated with both BMD (regression line = 0.79 to 0.0478 log predicted fracture;

8 ecreased the most during pregnancy (slope of regression line: -80 g x g N(-1) x d(-1); 95% CI: -129,

9 A fitted regression line also showed a decreasing trend (slope =

10 The mean slope of the EMG-GG-versus-DP regression lines also decreased to 23% of the control va

11 group showed a larger downward shift in the regression line and a much steeper negative slope (-2.08

12 Regression line and scattergram plot analyses determined

13 = 0.99), but comparison of the slopes of the regression lines (bDNA, m = 0.96; RT-PCR, m = 0.83) sugg

14 ification of diet in renal diseases formula) regression line before and after MMF initiation was +2.0

15 cally significant effect on the slope of the regression line between quantitative CT findings, FEV(1)

16 the venous return curve, we constructed the regression line between the pairs of cardiac index (puls

17 For these systems, the slope of the regression line between true and measured defect size wa

18 phosphorylation dose-dependently, while the regression lines between growth and ERK phosphorylation

19 h-1 (kg body wt)-1 (P < 0.05, comparison of regression lines by Student's t test), but had no effect

20 The scatterplot produces a regression line characterized by the following equation:

21 correlated (R(2) = 0.9), with a slope of the regression line close to unity and a negligible intercep

22 The regression line correlating the HCS-1 assay to the Ampli

23 was assessed by comparing the slopes of the regression lines derived from the reciprocal of serum cr

24 , resulted in a decrease in the slope of the regression line describing the relationship between cell

25 A regression line describing this relationship had a slope

26 Regression lines drawn for bifenazate showed that it fol

27 ogression rate was estimated from the linear regression line for all available radiographic time poin

28 the corresponding peak area from the linear regression line for clean (solute-free) MP, provided oth

29 Mixed effects models fit a unique linear regression line for each person using serial EF data.

30 For the myocardial infarction group, the regression line for log(power) on log(frequency) was shi

31 The regression line for pSP102 replication versus total DNA

32 ing exercise, in the central controller, the regression line for the P(a,CO(2))-minute ventilation (V

33 The slope of the regression line for the ray with greatest regression coe

34 The slope of regression lines for both readers plotting GE attenuatio

35 The regression lines for non-statin and statin trials were s

36 Although the slopes of the regression lines for R2' versus [Fe] and for R2 versus [

37 The slopes of the linear regression lines for standards in MPs with different con

38 The slope of the weighted regression line from the 2 data sources was 0.76 (SE=0.0

39 r kidney-pancreas transplants, the slopes of regression lines generated by plotting the reciprocal of

40 The slope of the regression line in the exposed infants did not differ st

41 Characteristics of the regression line included a slope of 0.98 and y intercept

42 exposure energy, with greater slopes of the regression lines indicating greater sensitivity to damag

43 or (99m)Tc-tetrofosmin, as inferred from the regression line intercept (0.14 vs. 0.38, respectively).

44 with correlation coefficients of all linear regression lines (measured intensity ratios vs mass rati

45 with correlation coefficients of all linear regression lines (measured intensity ratios vs mass rati

46 with correlation coefficients of all linear regression lines (measured intensity ratios vs mass rati

47 with correlation coefficients of all linear regression lines (measured intensity ratios vs mass rati

48 g Passing-Bablok regression revealed similar regression lines, no proportional bias, and improvement

49 anisms were assessed (1) by the slope of the regression line obtained from changes of RR interval and

50 The variance of the two regression lines obtained for each unit before and after

51 Deviation from the regression line of predicted angles to the postdeploymen

52 t perpendicular prosthesis projection to the regression line of predicted perpendicular projections w

53 The regression line of the ferritin concentration in menstru

54 For each patient the slope of the regression line of valve area to flow rate was determine

55 ethods, Passing-Bablok regression revealed a regression line of Y = (1.069 x X) - 0.346 (95% CI of th

56 The regression lines of all standard catechins were linear w

57 as pooled SD from the single-patient linear regression lines of ERPF versus time.

58 Regression lines of required CRRT urea K (ml/h) versus p

59 From these profiles, regression lines of required IHD frequency (per week) ve

60 ted from the slopes of the least-squares fit regression lines of the time-activity curves for the fir

61 llowed the construction of a semilogarithmic regression line per extract.

62 The correlation coefficients of all linear regression lines ranged from 0.998 to 1.000.

63 error of the estimate (RSEE) for the linear regression line ranging from 0.0131 to 0.1760 and 1.2 to

64 The negative slope of the regression line relating homocysteine and folate was sig

65 significantly lower than MBFT (slope of the regression line significantly different from 1, P < 0.00

66 CT-based correction (R(2) = 0.9956), with a regression line slope of 0.960.

67 mined by the peak amplitude versus amplitude regression line slope.

68 searchers should consider plotting the three regression lines that can be calculated for any two-dime

69 We fitted a locally weighted polynomial regression line to daily mortality to estimate the numbe

70 pressure and the inverse of the slope of the regression line to quantify resistance to venous return.

71 near (standard error of the estimate for the regression line was 0.0323) over 3 orders of magnitude,

72 The slope of the weighted regression line was 0.95 (SE=0.007), and the intercept w

73 ure concentrations, the slope of the type II regression line was 1 and nearly passed through the orig

74 A regression line was fit between density of specialist su

75 The regression line was not different between men and women,

76 r = 0.75, P < 0.0001), and the least-squares regression line was not significantly different from y =

77 Compared with the control arms, the statin regression line was significantly shifted leftward, such

78 The x-axis intercept of the regression line was used to estimate the mean systemic p

79 For the total subjects, the regression line was VFALBIA = 0.698 VFACT + 29.521, (cor

80 sions (pulmonary nodules, bone lesions); the regression line was y = 0.85x + 0.15, R(2) = 0.83, for t

81 In patients, the slope of the regression lines was also negligible (-0.69 < slope < 0.

82 vivo recovery, derived from the slope of the regression line, was 50%.

83 d TSC number, as defined by the slope of the regression line, was the same in LA and EDL muscles, ind

84 The slopes of the regression line were 0.97 and 0.76 at 6 and 18 hr, respe

85 lot with raw data and a corresponding fitted regression line were included in the analysis.

86 nd the variance of blood pressure about this regression line were tested for association with subsequ

87 ts of the data were created, and third-order regression lines were calculated.

88 e value of the gamma-intercept of the linear regression line with the corresponding peak area from th

89 th 3, and is well approximated by two linear regression lines with R2 values of 1.0 and 0.99.