Virulence of Pseudomonas aeruginosa involves the co-ordinate expression of a range of factors including type IV pili (tfp), the type III secretion system (TTSS) and quorum sensing. Tfp are required for twitching motility, efficient biofilm formation, and for adhesion and type III secretion (TTS)-mediated damage to mammalian cells. We describe a novel gene (fimL) that is required for tfp biogene...

Cyclic AMP (cAMP) is a signaling molecule that is involved in the regulation of multiple virulence systems of the opportunistic pathogen Pseudomonas aeruginosa. The intracellular concentration of cAMP in P. aeruginosa cells is tightly controlled at the levels of cAMP synthesis and degradation through regulation of the activity and/or expression of the adenylate cyclases CyaA and CyaB or the cAM...

We present a Bayesian sampling approach to parameter estimation in a discrete– response model with double rules of selectivity, where the dependent variables contain two layers of binary choices and one ordered response. Our investigation is motivated by an empirical study using such a double–selection rule for three labor–market outcomes, namely labor force participation, employment and occupa...

Pseudomonas aeruginosa, a ubiquitous bacteria found in diverse ecological niches, is an important cause of acute infections in immunocompromised individuals and chronic infections in patients with Cystic Fibrosis. One signaling molecule required for the coordinate regulation of virulence factors associated with acute infections is 3', 5'-cyclic adenosine monophosphate, (cAMP), which binds to an...

In this paper, Hamilton’s (1989) Markov-switching model is extended to the simultaneous equations model. Using a framework for an instrumental variable interpretation of full information maximum likelihood (FIML) by Hausman (1975), we can deal with the problem of simultaneous equations based on the Hamilton filter. When we compared the proposed FIML Markov-switching model to LIML Markovswitchin...

Pairwise maximum likelihood (PML) estimation method is developed for factor analysis models with ordinal data and tted both in an exploratory and con rmatory set-up. The performance of the method is studied via simulations and comparisons with full information maximum likelihood (FIML) and three-stage limited information estimation methods, namely the robust unweighted least squares (3S-RULS) a...

The performance of parameter estimates and standard errors in estimating F. Samejima's graded response model was examined across 324 conditions. Full information maximum likelihood (FIML) was compared with a 3-stage estimator for categorical item factor analysis (CIFA) when the unweighted least squares method was used in CIFA's third stage. CIFA is much faster in estimating multidimensional mod...

ÐMissing data are often encountered in data sets used to construct effort prediction models. Thus far, the common practice has been to ignore observations with missing data. This may result in biased prediction models. In this paper, we evaluate four missing data techniques (MDTs) in the context of software cost modeling: listwise deletion (LD), mean imputation (MI), similar response pattern im...

Average change in list recall was evaluated as a function of missing data treatment (Study 1) and dropout status (Study 2) over ages 70 to 105 in Asset and Health Dynamics of the Oldest-Old data. In Study 1 the authors compared results of full-information maximum likelihood (FIML) and the multiple imputation (MI) missing-data treatments with and without independent predictors of missingness. Re...

Item non-response occurs when respondents fail to provide answers to some or all of the questions posed during survey interviews. The standard procedure is to exclude such responses from the econometric analysis. This may be appropriate if the sample included does not differ significantly from those excluded in the analysis. If this is not the case, the econometric analyst faces a sample select...