LEADER 03683 am 2200733 n 450 001 9910306651903321 005 20240208201559.0 010 $a2-35613-295-3 024 7 $a10.4000/books.ausonius.10389 035 $a(CKB)4100000007522676 035 $a(FrMaCLE)OB-ausonius-10389 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/41145 035 $a(PPN)234054670 035 $a(EXLCZ)994100000007522676 100 $a20190408j|||||||| ||| 0 101 0 $afre 135 $auu||||||m|||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAquam in altum exprimere $eLes machines élévatrices d?eau dans l?Antiquité /$fAlain Bouet 210 $aPessac $cAusonius Éditions$d2018 215 $a1 online resource (169 p.) 311 $a2-910023-57-5 330 $aLes machines élévatrices d?eau ont été pendant longtemps méconnues dans l?Antiquité romaine car seule comptait l?eau courante et abondante amenée par les aqueducs. Pourtant de nombreux sites en ont livré plusieurs exemples depuis le xixe s., témoignages de la diversité des techniques. Ces dernières années, les découvertes se sont multipliées et permettent d?appréhender ces éléments fragiles car faisant souvent appel au bois, avec les méthodes d?étude les plus récentes. La Table-ronde organisée à Ausonius en 2003 a permis de faire le point de l?état des connaissances. In the ancient Roman world, where the plentiful supply of running water by the prestigious aqueducts was what mattered most, water-lifting devices remained largely unknown. Since the 19th century, however, a range of such devices, confirming the use of several different techniques, has been found in numerous sites. Moreover, as the number of such discoveries has increased in recent years, this has enabled the most up-to-date methods to be applied to these structures which, as wood elements are often used, are particulary fragile. Aquam in Altum Exprimere, the Round-table Study Day organized by Ausonius in 2003 has contributed to a general stocktaking of our present-day knowledge on this subject. 606 $aHydraulic machinery$xHistory$vCongresses 606 $aPumping machinery$xHistory$vCongresses 610 $aaqueduc 610 $apuit antique 610 $achaîne à godet 610 $anoria 610 $adistribution de l'eau 610 $amachine élévatrice d'eau 610 $ahistoire des techniques 615 0$aHydraulic machinery$xHistory 615 0$aPumping machinery$xHistory 686 $a6,12$2ssgn 686 $aLE 2003$2rvk 700 $aBlair$b Ian$01288481 701 $aBouet$b Alain$0739179 701 $a?au?evi?$b Morana$01288482 701 $aChevalier$b Pascale$01288483 701 $aCoadic$b Sophie$01288484 701 $aConche$b Frédéric$01288485 701 $aDescat$b Raymond$0258891 701 $aFleury$b Philippe$0171156 701 $aFogagnolo$b Stefania$0596049 701 $aFournier$b Francis$01288486 701 $aJacques$b Philippe$01288487 701 $aMarde?i?$b Jagoda$01288488 701 $aMorvillez$b Éric$01287423 701 $aPellecuer$b Christophe$01288489 701 $aPender$b Branko$01288490 701 $aPlassot$b Éric$01287449 701 $aSpain$b Robert$0603611 701 $aTata$b Margherita Bedello$01288491 701 $aTaylor$b Tony$0411066 701 $aTopi?$b Mira$01288492 701 $aBouet$b Alain$0739179 801 0$bFR-FrMaCLE 906 $aBOOK 912 $a9910306651903321 996 $aAquam in altum exprimere$93020883 997 $aUNINA LEADER 05372nam 2200673 450 001 9910811547103321 005 20230803220319.0 010 $a1-118-72198-5 010 $a1-118-72195-0 010 $a1-118-72196-9 035 $a(CKB)2550000001130061 035 $a(EBL)1471797 035 $a(OCoLC)860923490 035 $a(SSID)ssj0001002363 035 $a(PQKBManifestationID)11551095 035 $a(PQKBTitleCode)TC0001002363 035 $a(PQKBWorkID)10995861 035 $a(PQKB)10455825 035 $a(OCoLC)868971811 035 $a(MiAaPQ)EBC1471797 035 $a(Au-PeEL)EBL1471797 035 $a(CaPaEBR)ebr10784792 035 $a(CaONFJC)MIL530108 035 $a(EXLCZ)992550000001130061 100 $a20131109d2014 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aRegression methods for medical research /$fBee Choo Tai, David Machin 210 1$aChichester, West Sussex, UK :$cJohn Wiley and Sons,$d2014. 210 4$d©2014 215 $a1 online resource (313 p.) 300 $aDescription based upon print version of record. 311 $a1-4443-3144-2 311 $a1-299-98857-1 320 $aIncludes bibliographical references and index. 327 $aRegression Methods for Medical Research; Copyright; Contents; Preface; 1 Introduction; Introduction; Statistical models; Comparing two means; Linear regression; Types of dependent variables (y-variables); Some completed studies; Further reading; Technical details; Student's t-test; Linear regression; Predicting a mean value of y for a particular x; Predicting an individual's value of y for a particular x; Analysis of Variance (ANOVA); Coefficient of determination; Extending the simple linear model; Correlation; Logarithms and the exponential constant, e 327 $a2 Linear Regression: Practical IssuesTypes of covariates (independent variables); Ordered categorical covariates; Numerically discrete covariates; Unordered categorical covariates; Verifying the assumptions; Ordered categorical covariate; Continuous covariate; Do the assumptions matter?; Precautions; Computation; Simple models; Study design; Clinical and statistical significance; Reporting; Technical details; Global tests; Ordered Normal scores; 3 Multiple Linear Regression; Linear regression: two covariates; How good is the fitted model?; Quadratic models; Multiple linear regression 327 $aExtending the 2-covariate modelNotation; Interactions; Non-nested models; Precautions; Nested models; Collinearity; Parsimonious models; Verifying assumptions; Technical details; Nested models; Akaike's criterion; 4 Logistic Regression; The logit transformation; Odds ratio; The logit transformation; Logistic regression; Categorical and continuous covariates; Unordered categorical covariate; Ordered categorical covariate; Continuous covariate; Multiple logistic regression; Interactions; Model checking; Tabulations; Lack of an important covariate; Outlying or influential observations 327 $aGoodness-of-fitConditional logistic regression; Ordered logistic regression; Technical details; Odds ratio (OR) and relative risk (RR); Binomial distribution; Maximum likelihood estimation (MLE); Likelihood ratio (LR) test; The empirical logit transformation; 5 Poisson Regression; Introduction; Poisson or Binomial models; Unknown population size at risk; Over-dispersion and robust estimates; Over-dispersion; Robust procedures; Known population size at risk; Known cumulative exposure; Zero-inflated models; Residuals; Technical details; Poisson distribution; Maximum Likelihood Estimation (MLE) 327 $aRelationship between Poisson and logit models6 Time-to-Event Regression; Time-to-event data; Kaplan-Meier survival curve; The hazard rate and hazard ratio; Hazard ratio; The Cox regression model; Single covariate; Two covariates; More than two covariates; Verifying proportional hazards; Complementary log-log plot; Observed and predicted K-M plots; Schoenfeld residuals; What if the proportional hazards assumption is wrong?; Stratified Cox; Technical details; Calculating a Kaplan-Meier survival curve; The hazard function; The complementary log-log transformation; Residuals; 7 Model Building 327 $aIntroduction 330 $a Regression Methods for Medical Research provides medical researchers with the skills they need to critically read and interpret research using more advanced statistical methods. The statistical requirements of interpreting and publishing in medical journals, together with rapid changes in science and technology, increasingly demands an understanding of more complex and sophisticated analytic procedures.The text explains the application of statistical models to a wide variety of practical medical investigative studies and clinical trials. Regression methods are used to app 606 $aRegression analysis 606 $aMedicine$xResearch 615 0$aRegression analysis. 615 0$aMedicine$xResearch. 676 $a610.72/4 700 $aTai$b Bee-Choo$01658558 701 $aMachin$b David$f1939-$0520765 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910811547103321 996 $aRegression methods for medical research$94012646 997 $aUNINA