Structure and thermal reactivity of Zn(II) salts of isocinchomeronic acid (2,5-pyridinedicarboxylic acid)

The synthesis, an improved refined crystal and molecular structure re-determination, and the thermal decomposition behavior of two Zn(II) derivatives of isocinchomeronic acid (2,5-pyridinedicarboxylic acid or H(2)2,5-pydc) are presented. [Zn(2,5-pydc)(H(2)O)(3)Zn(2,5-pydc)(H(2)O)(2)](2) (1) crystallizes in the triclinic P-1 space group with a = 7.106(2), b = 11.450(2), c = 11.869(1) angstrom, alpha = 107.29(1), beta = 104.08(1), gamma = 90.32(2)degrees, and Z = 2. [Zn(2,5-pydc)(H(2)O)(2)] center dot H(2)O (2) is orthorhombic (P2(1)2(1)2(1) space group), with a = 7.342(1), b = 9.430(1), c = 13.834(2) angstrom, and Z = 4. The structures were refined to agreement R(1)-factors of 0.0315 (1) and 0.0336 (2). Complex (1) is arranged as molecular Zn(4)(2,5-pydc)(4)(H(2)O)(10) tetramers, the cages of which define channels that remain unblocked by anions. Compound (2) is polymeric with Zn(2,5-pydc)(H(2)O)(2) and Zn(2,5-pydc)(H(2)O)(3) units linked through bridging ligands. Both compounds were synthesized under mild conditions in aqueous media, without need to resort to hydrothermal media. Changing the pH from 4.51 to 5.75 suffices to direct the chemical processes toward the orthorhombic compound rather than to the triclinic one.

Hypothesis testing in an errors-in-variables model with heteroscedastic measurement errors

In many epidemiological studies it is common to resort to regression models relating incidence of a disease and its risk factors. The main goal of this paper is to consider inference on such models with error-prone observations and variances of the measurement errors changing across observations. We suppose that the observations follow a bivariate normal distribution and the measurement errors are normally distributed. Aggregate data allow the estimation of the error variances. Maximum likelihood estimates are computed numerically via the EM algorithm. Consistent estimation of the asymptotic variance of the maximum likelihood estimators is also discussed. Test statistics are proposed for testing hypotheses of interest. Further, we implement a simple graphical device that enables an assessment of the model`s goodness of fit. Results of simulations concerning the properties of the test statistics are reported. The approach is illustrated with data from the WHO MONICA Project on cardiovascular disease. Copyright (C) 2008 John Wiley & Sons, Ltd.