Based on data from my in-vitro investigation in the non-pulsatile flow test rig, my best estimate for the random (inter-reading) error was +/-10.0% (95% c.i.) for single and +/-5.8% for triplicate readings and the systematic (between catheters) error was +/-11.6%. Thus, the overall error was +/-15.3% for a single, and +/-13.0% for triplicate readings. / For the in-vitro model, a test rig through which water circulated at different rates with ports to insert catheters into a flow chamber was assembled. Flow rate was measured by an externally placed transonic flow probe and meter. The meter was calibrated by timed filling of a cylinder. Arrow and Edwards 7Fr thermodilution catheters, connected to a Siemens SC9000 cardiac output monitor, were tested. Thermodilution readings were made by injecting 5 mL of ice-cold water. Measurement error was divided into random and systematic components, which were determined separately. Between-readings (random) variability was determined for each catheter by taking sets of 10 readings at different flow rates. Coefficient of variation (CV) was calculated for each set and averaged. Between-catheters systems (systematic) variability was derived by plotting calibration lines for sets of catheters. Slopes were used to estimate the systematic component. Performances of three cardiac output monitors were compared: Siemens SC9000, Siemens Sirecust 1261, and Philips MP50. After the constant rate model, I also developed a pulsatile model and did a similar evaluation. / For the in-vivo model, ten domestic pigs, weight 27--32kg, were anaesthetized with propofol and ketamine infusion. The aortic flow probe was surgically placed via a left thoracotomy. A pulmonary artery catheter sheath was inserted in the right internal jugular vein. Both Arrow and Edwards catheters were used. A 10 ml, room temperature, saline injectate was used and cardiac output was calculated using the Seimens SC9000 monitor. Sets of cardiac output readings were taken over 5 minute intervals of stable haemodynamics. Catheters were frequently changed and cardiac output increased (e.g. Dopamine and Adrenaline) and decreased (e.g. Trinitrate and Beta-Blocker) using drug infusions. Baseline (e.g. no drug intervention) and drug treatment data were analyzed separately. / For the pulsatile model, the best estimate for the random (inter-reading) error (95% c.i.) was +/-16.7% for single and +/-9.7% for triplicate readings and the systematic (between catheters) error was +/-21.1 %. Thus, the overall error was +/-26.9% for a single, and +/-23.2% for triplicate readings. / I set out to evaluate in the pig model two types of measurement errors, random and systematic errors, which I defined using the test rig in-vitro, the coefficient of variation (CV) was +2.8% (95% c.i.), with random error (95% c.i.) of + 5.5%. But if the ranges of cardiac output was widened, the error was increased to + 19.3% . The systematic component ofthe error (95% c.i.) was +20.0%. / There was a good linear regression relationship between the two methods (e.g. thermodilution and flow probe). The mean correlation coefficient was 0.95 (0.9--0.99, 95% c.i.) based on data from 8 pigs'. However, there were significant systematic errors due to calibration of the measurement systems between pig experiment and catheter testings. By eliminating the systematic errors based on the calibration line corrections, I was able to draw modified Bland and Altman plots for the 8 pigs. The bias was eliminated and become 0 L/min. The limits of agreement or percentage errors of this analysis, were within the +/-30% limits. / Thermodilution cardiac output, measured using a pulmonary artery catheter and cardiac output monitor, is the reference standard against which all new methods of cardiac output measurement are judged. There has been a recent decline in the use of pulmonary artery thermodilution cardiac output in favour of less invasive methods. When validating these new methods comparisons are made using Bland and Altman analysis with single bolus thermodilution as the accepted reference method. 95% confidence intervals and percentage errors are generated that rely on a precision of +/-20% (Stetz et al (1982)) for thermodilution measurements. However, this precision is now being questioned as it is based on data collected over 30-years ago. Lack of precision of this reference standard, and uncertainty about its true values, causes difficulty when validating new cardiac output technology. Thus, the aim of this thesis was to reappraise the error of thermodilution by testing currently available catheters in both in-vitro and in-vivo settings. / When testing in haemodynamically unstable conditions (e.g. high and low flow states), the percentage error was increased by about +/-15% in the treatment groups comparing with baseline group data. This finding was in agreement with the growing world opinion that thermodilution may not be as accurate as originally thought, in extreme haemodynamic conditions, such as hypovolaemia or high cardiac output states. / Yang, Xiaoxing. / Adviser: Lester August Hall Critchley. / Source: Dissertation Abstracts International, Volume: 73-06, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (leaves 165-178). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

Thesis (M.S.)--University of Michigan, 1979.

Thesis (Ph. D.)--University of Pennsylvania, 1995. / Includes bibliographical references (leaves 293-303).

Thesis (M.S.)--University of Michigan, 1979.

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The effects of using the United States input-output table to explain Israel's economic structure was studied, by comparing price data generated on the basis of the U. S. tables and prices observed in the two countries. A substantial difference between prices generated and observed led to the conclusion that the technological structure of the United States cannot be used to approximate Israel's structure. Various adjustments were then applied to the United States coefficient matrix to determine if it could be transformed into a new technological structure which would more closely approximate Israel's economy. Significant improvements were noted by three of the adjustments while one showed no noticeable difference from the results obtained using the unadjusted U.S. matrix. One of the adjustments was found to transform the U.S. coefficient matrix into a new matrix which when multiplied by the observed final demand vector of Israel would predict accurately, output levels and effects of changes in the Israel economy.

Ranking and Selection procedures have been designed to select the best system from a number of alternatives, where the best system is defined by the given problem. The primary focus of this thesis is on experiments where the data are from simulated systems. In simulation ranking and selection procedures, four classes of comparison problems are typically encountered. We focus on two of them: Bernoulli and multinomial selection. Therefore, we wish to select the best system from a number of simulated alternatives where the best system is defined as either the one with the largest probability of success (Bernoulli selection) or the one with the greatest probability of being the best performer (multinomial selection). We focus on procedures that are sequential and use an indifference-zone formulation wherein the user specifies the smallest practical difference he wishes to detect between the best system and other contenders. We apply fully sequential procedures due to Kim and Nelson (2004) to Bernoulli data for terminating simulations, employing common random numbers. We find that significant savings in total observations can be realized for two to five systems when we wish to detect small differences between competing systems. We also study the multinomial selection problem. We offer a Monte Carlo simulation of the Bechhofer and Kulkarni (1984) MBK multinomial procedure and provide extended tables of results. In addition, we introduce a multi-factor extension of the MBK procedure. This procedure allows for multiple independent factors of interest to be tested simultaneously from one data source (e.g., one person will answer multiple independent surveys) with significant savings in total observations compared to the factors being tested in independent experiments (each survey is run with separate focus groups and results are combined after the experiment). Another multi-factor multinomial procedure is also introduced, which is an extension to the MBG procedure due to Bechhofer and Goldsman (1985, 1986). This procedure performs better that any other procedure to date for the multi-factor multinomial selection problem and should always be used whenever table values for the truncation point are available.