1 compared in the phantom experiment by using
multiple linear regression analysis.
2 tal and occipital regions (both p < 0.01) in
multiple linear regression analysis.
3 and beta = 0.45 [P = .076], respectively) in
multiple linear regression analysis.
4 fter correction for baseline differences and
multiple linear regression analysis.
5 were used to develop predictive models with
multiple linear regression analysis.
6 betaine with tHcy were investigated by using
multiple linear regression analysis.
7 of mean RV E(LL) (beta = .19, P = .005) in a
multiple linear regression analysis.
8 d the intraclass correlation coefficient and
multiple linear regression analysis.
9 rinsic DMN connectivity were investigated by
multiple linear regression analysis.
10 atrophy in both the antrum and the corpus by
multiple linear regression analysis.
11 colocalization analysis and 16-23 Hz in the
multiple linear regression analysis.
12 e for Depression scores) were examined using
multiple linear regression analysis.
13 earman rank correlation coefficient (rs) and
multiple linear regression analysis.
14 lyses were performed with Student t test and
multiple linear regression analysis.
15 plant recipients by the use of mixed effects
multiple linear regression analysis.
16 d to serum alpha-tocopherol concentration in
multiple linear regression analysis.
17 imental variables was identified by stepwise
multiple linear regression analysis.
18 ent and prevalent patients, when assessed by
multiple linear regression analysis.
19 In
multiple linear regression analysis,
accounting for TNFR
20 changes in LM and aLM was examined by using
multiple linear regression analysis adjusted for potenti
21 relation coefficients (r) were obtained from
multiple linear regression analysis adjusting for age, a
22 In
multiple linear regression analysis (
adjusting for total
23 The tested hypothesis was evaluated through
multiple linear regression analysis,
after control for p
24 In the
multiple linear regression analysis,
after controlling f
25 By
multiple linear regression analysis,
age (p < 0.001), di
26 In
multiple linear regression analysis,
an absence of compl
27 A
multiple linear regression analysis and bootstrapping we
28 sum test, Spearman correlation coefficient,
multiple linear regression analysis,
and Lin correlation
29 Student t test,
multiple linear regression analysis,
and Spearman correl
30 A
multiple linear regression analysis,
controlled for sex,
31 However,
multiple linear regression analysis detected genetic eff
32 Further, a
multiple linear regression analysis determined the relat
33 Multiple linear regression analysis examined the separat
34 investigated any within-subject changes, and
multiple linear regression analysis explored between-sub
35 ese results provide confidence in the use of
multiple linear regression analysis for predicting solvo
36 Multiple linear regression analysis found arm span, race
37 Multiple linear regression analysis found testosterone a
38 In a stepwise
multiple linear regression analysis,
gender and previous
39 Multiple linear regression analysis indicated that 25(OH
40 A
multiple linear regression analysis indicated that CMV d
41 Multiple linear regression analysis indicated that sex,
42 By stepwise and
multiple linear regression analysis,
LA dP/dt(max) was b
43 On
multiple linear regression analysis,
methadone doses (P
44 On
multiple linear regression analysis,
minimal lumen diame
45 obtained by a recently introduced algorithm,
multiple linear regression analysis (
MLR) of the equatio
46 Multiple linear regression analysis of measured concentr
47 Multiple linear regression analysis of PCA texture compo
48 Multiple linear regression analysis of the relation betw
49 Multiple linear regression analysis of voltammograms dem
50 Multiple linear regression analysis revealed a significa
51 In this group of 20 patients,
multiple linear regression analysis revealed a trend bet
52 On the basis of these parameters,
multiple linear regression analysis revealed maximum ach
53 Multiple linear regression analysis revealed prior beta-
54 Multiple linear regression analysis revealed significant
55 Multiple linear regression analysis revealed that intens
56 Multiple linear regression analysis revealed that only M
57 Multiple linear regression analysis revealed that the hi
58 Multiple linear regression analysis revealed that wherea
59 Multiple linear regression analysis reveals (1) a signif
60 Multiple linear regression analysis showed a significant
61 Multiple linear regression analysis showed that age and
62 Multiple linear regression analysis showed that apparent
63 Multiple linear regression analysis showed that both age
64 Multiple linear regression analysis showed that glycated
65 Multiple linear regression analysis showed that patients
66 Stepwise
multiple linear regression analysis showed that the asso
67 Multiple linear regression analysis showed that the plas
68 Multiple linear regression analysis showed that the reti
69 In
multiple linear regression analysis,
socioeconomic facto
70 Multiple linear regression analysis suggested that Cr(VI
71 Multiple linear regression analysis suggested that the b
72 jects eating 20 different diets, we found by
multiple linear regression analysis that RNAE [mEq/d x 1
73 The finding in
multiple linear regression analysis that weight gain dur
74 On the basis of
multiple-linear-regression analysis that adjusted for po
75 We used
multiple linear regression analysis to compare SMC with
76 We used
multiple linear regression analysis to determine the eff
77 Using
multiple linear regression analysis,
total calcium score
78 The
multiple linear regression analysis using CAL (dependent
79 In
multiple linear regression analysis,
vessel size was pos
80 Multiple linear regression analysis was conducted to ide
81 nadian Health Measures Survey, and a 2-stage
multiple linear regression analysis was conducted.
82 riventricular hyperintensities, and stepwise
multiple linear regression analysis was performed for fa
83 A hierarchical
multiple linear regression analysis was performed to ass
84 Multiple linear regression analysis was performed to det
85 Multiple linear regression analysis was performed to ide
86 Multiple linear regression analysis was performed to wei
87 Multiple linear regression analysis was used on 11-year
88 A
multiple linear regression analysis was used to correlat
89 Multiple linear regression analysis was used to derive s
90 Multiple linear regression analysis was used to describe
91 Multiple linear regression analysis was used to determin
92 Multiple linear regression analysis was used to evaluate
93 Multiple linear regression analysis was used to examine
94 Multiple linear regression analysis was used to identify
95 Multiple linear regression analysis was used to identify
96 Multiple linear regression analysis was used.
97 Multiple linear-regression analysis was used to determin
98 rank sum test, Spearman rho correlation, and
multiple linear regression analysis were performed.
99 sformed adiponectin levels were evaluated by
multiple linear regression analysis with interaction ter
100 Multiple linear regression analysis with stepwise variab