ライフサイエンスコーパス: goodness-of-fit

1 hin this study using Hosmer-Lemeshow C test (goodness-of-fit).

2 me at the cost of reduced model reliability (goodness-of-fit).

3 as against weak results did not diminish the goodness of fit.

4 curacy and does not significantly reduce the goodness of fit.

5 ng, unconfounded by auditory acuity or model goodness of fit.

6 aximizes either the effect estimate or model goodness of fit.

7 of death increased slightly in magnitude and goodness of fit.

8 tics including graphs are used to assess the goodness of fit.

9 ared error (RMSE) as statistical measures of goodness of fit.

10 ependently associated with MINS and improves goodness of fit.

11 ive graphical tests are applied to judge the goodness of fit.

12 calculated to quantify model complexity and goodness of fit.

13 riate regression analyses were evaluated for goodness of fit.

14 ous calibrations, yielding an improved final goodness of fit.

15 the 3 regression models was used to evaluate goodness of fit.

16 els demonstrated a similar degree of overall goodness-of-fit.

17 omial and allometric models yielded adequate goodness-of-fit.

18 The C-statistics (0.77) and Hosmer-Lemeshow goodness of fit (0.9) for recipient risk score using der

19 e area, 0.842+/-0.023) and calibration (chi2 goodness of fit, 8.95; P=0.442).

20 0.934) and calibration (chi-square test for goodness-of-fit = 9.31, p = 0.317) of the PEdiatric Logi

21 In an attempt to improve the goodness of fit, a probabilistic model of late loss was

22 Our base-case LUR models had modest goodness-of-fit (adjusted R(2): approximately 0.5 [PN],

23 Goodness-of-fit analyses reveal that the irregularity in

24 e fitted to the MTP data, in accordance with goodness-of-fit analysis (coefficients of variation, sum

25 Results were evaluated with goodness-of-fit analysis and, in normal-appearing liver

26 Finally, a goodness-of-fit analysis applied at the individual subje

27 Goodness-of-fit analysis of each connectivity map with n

28 The Harrell C-index was used for goodness-of-fit analysis.

29 The results showed a great goodness of fit and accuracy for predicting the antioxid

30 ensive statistical analysis to determine the goodness of fit and calculate confidence intervals of fl

31 Robustness of the models was explored using goodness of fit and correlation.

32 The goodness of fit and discrimination power was compared us

33 , the CAD consortium scores offered improved goodness of fit and discrimination; thus, their use coul

34 deling resulted in a model with an excellent goodness of fit and in which the APOE x age interaction

35 ootstrap procedure to serve as the basis for goodness of fit and model selection with a single observ

36 rtz model providing the best balance between goodness of fit and number of parameters.

37 methods of statistical analysis, chi-squared goodness of fit and one proportion tests.

38 A chi2 test for goodness of fit and partial Fourier analysis were used t

39 dition, modeled functions were evaluated for goodness of fit and the statistical significance of thei

40 Models were tested for goodness of fit and were validated for the remaining 5,8

41 discrimination assessed via Hosmer-Lemeshow goodness-of-fit and C-statistics, respectively.

42 Goodness-of-fit and calibration were assessed by the Hos

43 ing trial (IDEAL; n=8888) confirmed adequate goodness-of-fit and calibration, but moderate discrimina

44 properties during cladogenesis, and performs goodness-of-fit and categorical statistical tests.

45 realistic modeling approach, yields superior goodness-of-fit and more reliable analysis results, as d

46 We then determined goodness-of-fit and optimal cutoff values through receiv

47 ell-established R(2) statistic for assessing goodness-of-fit and prediction power.

48 lop the models and subsequently evaluated by goodness-of-fit and receiver operating characteristic (R

49 ensive statistical analyses including error, goodness-of-fit and robustness assessments.

50 ear regression analyses assessing precision, goodness of fit, and accuracy to develop improvements in

51 n plots and Akaike Information Criterion for goodness of fit, and net reclassification improvement (N

52 Harrell's concordance statistic assessed goodness-of-fit, and then, Cox proportional hazard model

53 with the 2 IFs were compared regarding their goodness of fit as assessed by the residuals, fit parame

54 situations where two models possess similar goodness-of-fit assessments, visual analysis of the Cot

55 ple procedures for inference, prediction and goodness-of-fit assessments.

56 death rates of bacteria: these improved the goodness-of-fit at the second time point at the expense

57 of exposure prediction improved the model's goodness of fit (Bayesian Information Criterion) and led

58 tion ("return movements") by quantifying the goodness of fit between neuronal discharge during cued a

59 distributions, and calculate a least-squares goodness of fit between the two.

60 orrespondence, based on visual assessment of goodness of fit, between predicted and observed risk of

61 used, all tested models displayed comparable goodness of fit, but when different subranges of this po

62 each cluster's gene expression function and goodness-of-fit by way of a 'mean curve' construct and i

63 hort 2: C statistic = 0.887, Hosmer-Lemeshow goodness-of-fit C statistic chi-square = 39).

64 hort 1: C statistic = 0.874, Hosmer-Lemeshow goodness-of-fit C statistic chi-square = 72.5; cohort 2:

65 s, Kaplan-Meier methods (log-rank test), and goodness of fit calculations (c-statistics) were perform

66 D based on the standard normal distribution (goodness of fit chi(2) = 4.84, P = 0.01).

67 urve, 0.82) and calibration (Hosmer-Lemeshow goodness-of-fit chi-square p = 0.57) in the validation c

68 pared against the expected ratio of 1:2:1 by goodness-of-fit chi-square tests.

69 nd predicted diabetes risks (Hosmer-Lemeshow goodness-of-fit chi-squared test for each model: P < 0.0

70 CFA results did not show adequate goodness of fit (chi(2)(1025) = 2112.35, p < 0.001; CFI

71 ved by prescreening gene combinations with a goodness-of-fit chi2 statistic that depends on associati

72 Goodness-of-fit chi2 tests further indicated that partic

73 mplitude, acrophase, circadian quotient, and goodness-of-fit coefficient) derived from single-oscilla

74 g a shape-matching function that provides a 'goodness of fit' coefficient should provide a more robus

75 of ISRES+ estimates parameters with a higher goodness-of-fit compared with ISRES.

76 characteristic analyses and bootstrap-based goodness-of-fit comparisons via Bayesian information cri

77 ar [Spearman rank-order (rs)] and nonlinear (goodness-of-fit) correlations were performed.

78 ionally using the experimental KIE values as goodness of fit criteria.

79 del that best described these data, based on goodness-of-fit criteria, included first-order rate cons

80 timal number of classes was defined based on goodness-of-fit criteria, interpretability, and clinical

81 As a consequence, certain goodness-of-fit criteria, such as the runs-of-signs test

82 Based on visual inspection and goodness-of-fit criteria, the negative-flux lower bounda

83 on hypotheses, each validated by a composite goodness-of-fit criterion.

84 Goodness-of-fit demonstrated p value of more than 0.05 f

85 ated and best-fit models achieved sufficient goodness of fit (each P > 0.10).

86 The Hosmer-Lemeshow chi-square goodness-of-fit evaluations demonstrated absence of sign

87 cription length criterion was used to assess goodness of fit for each model.

88 an squared error (RMSE) was used to evaluate goodness of fit for each regression model.

89 Using the OLTX-specific approaches, goodness-of-fit for both hospital and 1-yr mortality was

90 is paper, we propose some tests to check the goodness-of-fit for the fixed and random effect models w

91 To estimate the goodness-of-fit for the Simplified Acute Physiology Scor

92 aluated, and all the models resulted in high goodness-of-fit for the training set with R(2) > 0.931 f

93 The resulting goodness of fit [Formula: see text] was roughly halved v

94 ormula: see text] [Formula: see text], and a goodness of fit [Formula: see text]).

95 e distributions are used to produce relative goodness-of-fit (GF) scores for measuring the difference

96 ) event ratios, and Greenwood-Nam-D'Agostino goodness-of-fit (GND) statistics, overall and in subgrou

97 eus and the global connectivity indexed with goodness of fit (GOF) of the default mode network (DMN)

98 Goodness of fit (GOF) test approaches for selecting prob

99 LS linear regression resulted in an improved goodness of fit (GOF), although the weighting factor sho

100 of lymphatic filariasis, and use a simulated goodness-of-fit (GOF) method to estimate immunological p

101 of the genes in the gene set are non-null, a goodness-of-fit (GOF) test can be used to compare whethe

102 More generally, we'd like to conduct a goodness-of-fit (GOF) test to check the model being used

103 elop the GoFAE-DND, an autoencoder that uses goodness-of-fit (GoF) tests as a regularizer.

104 Most goodness-of-fit (GOF) tests attempt to discern a preferr

105 Recently, two frequentist goodness-of-fit (GOF) tests were proposed to assess the

106 ratio: 0.99, 0.99, and 1.00; Hosmer-Lemeshow goodness of fit H-statistic: 66.4, 63.7, and 81.4 for th

107 ibration model method resulted in acceptable goodness of fit (Hosmer-Lemeshow test, P = 0.54; Brier s

108 del, but when tested across deciles of risk, goodness-of-fit (Hosmer-Lemeshow statistic, chi-square =

109 Goodness-of-fit improvements were assessed with the like

110 roved predictive performance, as measured by goodness of fit in a likelihood ratio test (P-value: <0.

111 ssion tree methods, modified to optimize for goodness of fit in treatment effects and to account for

112 However, in practice, the goodness-of-fit in meta-analysis is rarely discussed.

113 m-of-square-error (SSE) was used to evaluate goodness-of-fit in model calibration and prediction.

114 usted goodness-of-fit index, 0.89; parsimony goodness-of-fit index, 0.60; and root mean square error

115 0.94; goodness-of-fit index, 0.93; adjusted goodness-of-fit index, 0.89; parsimony goodness-of-fit i

116 18 (p < 0.001); comparative fit index, 0.94; goodness-of-fit index, 0.93; adjusted goodness-of-fit in

117 Goodness of fit indicated that, at realistic noise level

118 ains an extensive set of derived properties, goodness-of-fit indicators, and links to other EBI datab

119 The results from the goodness-of-fit indices of structural equation modeling

120 Model goodness of fit is evaluated over the temperature range

121 Then, the model goodness of fit is penalized by some suitable function o

122 different models were evaluated in terms of goodness-of-fit, long-term trends, and halving times.

123 null; selecting the lag that maximizes model goodness of fit may lead to confidence intervals that ar

124 ell both visually as well as in terms of the goodness of fit measure total mean squared error.

125 of variables as the decline in pseudo-R2 (a goodness-of-fit measure for median regression) when omit

126 with a maximum likelihood procedure and the goodness-of-fit measures along with the associated stand

127 Moreover, general goodness-of-fit measures are not a strong basis to suppo

128 s, to consider several model outcomes beyond goodness-of-fit measures in model evaluation, to use mod

129 rth-versus-first-quartile odds ratios (ORs), goodness-of-fit measures, and contributing fraction.

130 dataset, eBird, based on model selection and goodness-of-fit measures.

131 nality reduction methods by applying several goodness-of-fit measures.

132 The data showed a linear log-log plot and goodness-of-fit methods showed the data followed a power

133 e set of non-identifiable parameters and the goodness-of-fit metric or likelihood studied in typical

134 scriptive power of each model, using several goodness-of-fit metrics and a study of parametric identi

135 ros (all free parameters), provided the best Goodness of Fit of 0.0078 for Chi-Square difference test

136 , the pairwise regression formula revealed a goodness of fit of 0.792.

137 _cal and simultaneously measured mPAP with a goodness of fit of 0.892.

138 ution of the water-rich permeate flux with a goodness of fit of 0.92.

139 Goodness of fit of correlations between the IRC and SRF

140 The goodness of fit of each model to the new data set was te

141 The goodness of fit of models based on point counts ranged b

142 Area under the curve (AUC) and goodness of fit of prespecified logistic models, includi

143 racy and has often been used to evaluate the goodness of fit of the assumed models in settings other

144 rug release from varied CAC Ace-DEX NPs, the goodness of fit of the developed diffusion-erosion model

145 The goodness of fit of the logistic regression model was ass

146 A standard deviation score plot confirmed goodness of fit of the models, and fitted centiles were

147 deduced from differences in the statistical goodness of fit of the phosphotransfer data to the kinet

148 tandard statistical techniques to assess the goodness of fit of the resulting model and validate the

149 ive studies, the authors focused on relative goodness of fits of the various pathways, but a simple t

150 Goodness-of-fit of biomass data from fish stock assessme

151 The overall goodness-of-fit of both models was assessed.

152 In this study we compared the goodness-of-fit of each theory with a probabilistic mode

153 ogically meaningful parameters; assesses the goodness-of-fit of inferred cell clusters, trajectories

154 oth to measure and to visualize directly the goodness-of-fit of packing interactions.

155 on analysis of absolute levels of miRNAs and goodness-of-fit of predictors identified a linear combin

156 which quickly provide global measures of the goodness-of-fit of the 3D structures with NOESY peak lis

157 posed tests are useful tools in checking the goodness-of-fit of the normal models used in meta-analys

158 be used as a statistic for testing the model goodness-of-fit of the observed DNA sequences.

159 We discuss methods for assessing the goodness-of-fit of these models, as well as problems con

160 t measures that can be used to evaluate the "goodness-of-fit" of the 3D structure with NOESY data, to

161 The RPF server measures the 'goodness-of-fit' of the 3D structure with NMR chemical s

162 account for this pattern and was tested for goodness of fit on 55 individuals who became diabetic af

163 tion and the anomalous one, and to judge the goodness of fit on log-log plots.

164 onstrated that LTMG has significantly better goodness of fitting on an extensive number of scRNA-seq

165 (C-statistics 0.75, 0.78 and Hosmer-Lemeshow goodness of fit P = 0.4, 0.3, respectively).

166 oor discrimination (c=0.62) and calibration (goodness of fit P<0.001) for survival at 30 days.

167 statistic 0.75, 0.81 and the Hosmer-Lemeshow goodness-of-fit p = 0.49, 0.53, respectively) suggesting

168 well calibrated (Hosmer-Lemeshow chi-square goodness-of-fit P = 0.55).

169 The Hosmer-Lemeshow goodness-of-fit p value was 0.28, and the area under the

170 ) and excellent calibration (Hosmer-Lemeshow goodness-of-fit p-value 0.990).

171 s and had a c-statistic value of 0.957 and a goodness-of-fit p-value of 0.527.

172 r operator curve of 0.80 and Hosmer-Lemeshow goodness-of-fit P=0.22.

173 d on visual inspection of calibration plots (goodness-of-fit P=0.57).

174 he CAD consortium clinical provided adequate goodness of fit (P=0.39).

175 e C-statistic (0.78) and the Hosmer-Lemeshow goodness-of-fit (p = 0.89) in the model-development coho

176 83 and 0.85, respectively), and calibration (goodness of fit, p = .33 and p = .16, respectively).

177 oups and the predictions based on InTIME II (goodness-of-fit, p=0.7).

178 on, by estimating appropriate cutoffs of the goodness of fit parameter at prescribed error rates.

179 ients from ONA subjects (quality parameters: goodness-of-fit parameter [R(2)] = 0.81 and goodness-of-

180 it by simultaneous minimization of the chi 2 goodness-of-fit parameter and maximization of a statisti

181 as output calculated secondary structures, a goodness-of-fit parameter for the analyses, and tabular

182 Results: Goodness-of-fit parameters show that a monoexponential f

183 the best fits to the data, according to the goodness-of-fit parameters, due primarily to absence of

184 open the door to the development of modified goodness-of-fit procedures with wide applicability and g

185 ecision tree regression algorithm, shows the goodness of fit R(2) of 0.94 was achieved with an RMSE v

186 y and neutron scattering curve fits gave low goodness-of-fit R factors for 28 IgG1 and 2748 IgG4 stru

187 a linear calibration curve, which achieved a goodness of fit (R(2)) above 0.98.

188 distinct from the one used for calibration) goodness-of-fit (R (2) ) ranging from 0.37 to 0.89 and n

189 odel (clinical variables only) increased the goodness-of-fit (R(2)) from 0.05 to 0.42 and 0.19, respe

190 T1, ECV and goodness-of-fit (R(2)) values of the T1 times were calcu

191 corporated 7, 6, and 6 biomarkers to achieve goodness-of-fit R2 values of 0.769, 0.617, and 0.962, re

192 A goodness-of-fit (R2) statistic was used to determine the

193 A was demonstrated by the strength of IVIVC; goodness of fit ranged from 0.53 (DIN-I) to 0.74 (UBM-I)

194 ies for organisms justified primarily on the goodness of fit rather than on any biological mechanism.

195 Goodness-of-fit ratings of 10 DSM-IV-TR and 37 ICSD-2 in

196 od linearity (40-1000 pg PhIP/g hair) with a goodness-of-fit regression value of r(2) > 0.9978.

197 Analyses assessing goodness-of-fit, repeatability, and generality of the RF

198 on using the Harrell C-index and chi-squared goodness of fit, respectively, within both validation co

199 A goodness-of-fit score was computed for 555,000 unique pa

200 After a test for goodness-of-fit, separate analyses for diabetic patients

201 combining humidity and temperature, reduced goodness of fit slightly.

202 x may simply reflect the limitations of this goodness of fit statistic to assess model calibration.

203 rval, 0.996-1.040) and a low Hosmer-Lemeshow goodness-of-fit statistic (11.62; p = .31).

204 ical model was 0.77, and the p value for the goodness-of-fit statistic was .34.

205 .76, and the p value for the Hosmer-Lemeshow goodness-of-fit statistic was .60.

206 81), and the p value for the Hosmer-Lemeshow goodness-of-fit statistic was .89.

207 The Hosmer-Lemeshow goodness-of-fit statistic was 10.6 (p = 0.225) for the i

208 C statistic, Hosmer-Lemeshow goodness-of-fit statistic, and Brier's score measured pr

209 6) and adequate calibration (Hosmer-Lemeshow goodness-of-fit statistic, p = 0.80).

210 calibration (nonsignificant Hosmer-Lemeshow goodness-of-fit statistic, P =.54).

211 eristic curve of 0.736, with Hosmer-Lemeshow goodness-of-fit statistics of 7.19; P = .52.

212 ing multivariable Cox, Fine-Gray models, and goodness-of-fit statistics to investigate the relative i

213 empirical distributions of two conventional goodness-of-fit statistics were affected by the values o

214 d and 38-item FVQ_Young Person versions have goodness-of-fit statistics within the interval 0.5, 1.5

215 ted using area under the ROC curve (AUC) and goodness-of-fit statistics.

216 ination and calibration (C statistic = 0.86, goodness-of-fit statistics; p > .20).

217 els obtained within this study showed a high goodness-of-fit suggesting that the pH and the baking ti

218 The resulting goodness of fit suggests that neurons in motor cortex do

219 aike Information Criterion is used to assess goodness of fit, taking into account the number of unkno

220 s evaluated by measuring the Hosmer-Lemeshow goodness of fit test and calibration curve.

221 tes of heritability; and (iv) we developed a goodness of fit test based on the correlation of viral l

222 The Hosmer-Lemeshow goodness of fit test indicated that the predictive model

223 Although the power-law model failed the goodness of fit test, after incorporating social network

224 (discrimination) and by the Hosmer-Lemeshow goodness-of-fit test (calibration).

225 tatus Epilepticus Severity Score (chi-square goodness-of-fit test = 1.39; p = 0.845).

226 The PBMS NLME method was performed using the goodness-of-fit test and Akaike weight to select the bes

227 Harrell C index, a modified Hosmer-Lemeshow goodness-of-fit test and calibration curves, and reclass

228 el); C-statistic and 95% CI; Hosmer-Lemeshow goodness-of-fit test and calibration plots; and sensitiv

229 on diversity index and the p-value from x(2) goodness-of-fit test are calculated to measure its stati

230 well as good calibration (as measured by the goodness-of-fit test comparing observed to expected coun

231 quantile regressions were evaluated using a goodness-of-fit test derived from the cumulative sum of

232 We also propose a goodness-of-fit test for discriminating rejections due t

233 d by this problem we propose a nonparametric goodness-of-fit test for two empirical distributions of

234 y of observed against predicted outcomes and goodness-of-fit test indicated good calibration of the s

235 The three-level goodness-of-fit test indicated satisfactory performance

236 Software for the goodness-of-fit test is available as a Julia package at

237 A goodness-of-fit test revealed that DR-DQ haplotype shari

238 e representation of data, which are based on goodness-of-fit test statistics and standard errors of p

239 l using various model selection criteria and goodness-of-fit test statistics.

240 The goodness-of-fit test suggests that the phylogenetic mode

241 atio test of selection in conjunction with a goodness-of-fit test supports the selection hypothesis o

242 We also propose a goodness-of-fit test to aid investigators in determining

243 or the observed number of conversions, and a goodness-of-fit test to compare the observed number of c

244 rse Gaussian frailty was applied following a goodness-of-fit test to identify predictors of time to r

245 We propose here a goodness-of-fit test to quantify the fit between data ob

246 tatistically significant and Hosmer-Lemeshow goodness-of-fit test was run to ascertain the fitness of

247 el C index) and calibration (Hosmer-Lemeshow goodness-of-fit test) for prediction of in-hospital and

248 e (A) (purine to purine) (p<0.001, Pearson's goodness-of-fit test).

249 bration (P = .33 vs P = .02, Hosmer-Lemeshow goodness-of-fit test).

250 From the goodness-of-fit test, a critical percentage for each adm

251 ve of 0.80) and calibration (Hosmer-Lemeshow goodness-of-fit test, P = 0.102) when applied to the ADR

252 monstrated good calibration (Hosmer-Lemeshow goodness-of-fit test, P = 0.71) and discrimination (c-st

253 -recall curve (AUCPR), Hosmer-Lemeshow (H-L) goodness-of-fit test, precision, sensitivity, accuracy,

254 Using a chi-squared goodness-of-fit test, we identified 10 amino acid sites

255 g and validation samples as indicated by the goodness-of-fit test, which evaluated standardized nosoc

256 E are commonly performed using a simple chi2 goodness-of-fit test.

257 tudied using the Greenwood Nam-D'Agostino x2 goodness-of-fit test.

258 was evaluated with the Gronnesby and Borgan goodness-of-fit test.

259 logistic curve-fit evaluated by a Chi-square goodness-of-fit-test, receiver operating characteristic

260 Goodness-of-fit testing indicated excellent model calibr

261 Segregation analysis and goodness-of-fit testing of genetic models suggest that r

262 f the validity of a scoring system--and chi2 goodness-of-fit testing with data from 197 patients.

263 ating characteristic curve) and calibration (goodness-of-fit testing).

264 tests, the chi 2 and the Kolmogorov-Smirnov goodness of fit tests.

265 These model fits can pass a host of standard goodness-of-fit tests and other model-selection diagnost

266 Goodness-of-fit tests and receiver operating characteris

267 However, goodness-of-fit tests found that even bounded power-law

268 Goodness-of-fit tests indicated that this PRS was well c

269 e study of animal demography include running goodness-of-fit tests on a general starting model.

270 Surprisingly, goodness-of-fit tests reveal that this class of phenotyp

271 ing 1- and 2-tissue-compartment models, with goodness-of-fit tests showing a preference for the 2-tis

272 Goodness-of-fit tests strongly supported the fit of the

273 evaluate discrimination and Hosmer-Lemeshow goodness-of-fit tests to evaluate calibration.

274 (T classes vs. T + 1 classes) and chi-square goodness-of-fit tests were evaluated using parametric bo

275 Goodness-of-fit tests were more sensitive than the recei

276 e show, however, that despite passing common goodness-of-fit tests, PP-GLMs estimated from data are o

277 d a small number of alleles, and approximate goodness-of-fit tests.

278 g control, compared with the C statistic and goodness-of-fit tests.

279 assessed through prediction diagnostics and goodness-of-fit tests.

280 libration was assessed using Hosmer-Lemeshow goodness-of-fit tests.

281 f CLS parameters provided better measures of goodness of fit than Goldmann IOP parameters (mean, peak

282 tiplicative model had a substantially better goodness of fit than the additive model.

283 performed with the Hosmer-Lemeshow test for goodness of fit to generate odds ratios for possible ris

284 over all ages and provided close measures of goodness of fit to the data.

285 ully calibrated with an acceptable composite goodness-of-fit to clinical populations across multiple

286 mental dataset and compare the estimates and goodness-of-fit to those obtained by maximum likelihood

287 e-corrected stochastic block model, based on goodness-of-fit, to model networks of injection drug use

288 contributions and a slight reduction in the goodness-of-fit value (f ').

289 )/PET(100%), PET intensity correlation had a goodness-of-fit value of 0.94 versus 0.81, PSNR was 58.1

290 Goodness of fit values (R2) were near unity (.94 to .97)

291 o identify the features of interest, and the goodness of fit was assessed on the basis of R(2) values

292 Goodness of fit was assessed to determine the optimal b

293 Goodness of fit was indicated by the residual standard d

294 Excellent goodness-of-fit was also found for patient groups strati

295 The model's goodness-of-fit was assessed using the Hosmer-Lemeshow t

296 ra and provide a quantitative measure of the goodness of fit, which can be used to distinguish isomer

297 The resulting conformer pools balance goodness-of-fit with ligand strain.

298 factor analysis (EFA) was indicative of the goodness-of-fit with two factors (root mean square error

299 ormation) are filtered on the basis of their goodness-of-fit with unassigned NOESY peak lists using t

300 election, with simulation, and assessment of goodness of fit, with duplication-divergence model fits