Treatment integrity in completing critical steps of discrete-trial and backward chaining procedures were measured using a multiple baseline design across participants, counterbalanced for procedures.
Chaining procedures are widely utilized to define genomic intervals that are consistently ordered and oriented in multiple genomes and are often labeled as syntenic (Bourque et al., 2004; Dewey, 2007; Dubchak et al., 2009; Kent et al., 2003; Paten et al., 2008; Pevzner and Tesler, 2003).
Each dog experienced a total of 14 conditions, including baseline conditions (i.e., rates of preferred item release on request before any training), treatment conditions (i.e., different steps of the backward chaining procedure, such as release or place, sit), and probe conditions (i.e., same procedure as baseline but conducted after varying steps during treatment condition).
In Mugsy, we implement a new graph-based chaining procedure that looks for LCBs in the alignment graph and has similarities with previous methods for defining syntenic regions.
A double bind-organisation is thus missing the unique chance of learning from these mistakes, thereby losing the possibility to adapt production chains, procedures or any other vital management decisions in due time; or to fine-tune the company's steps towards a future and solution-orientated direction.
Monte Carlo Markov Chain procedures were implemented using the RJAGS package to call JAGS version 2.1.0 from R [35].
We used program default settings for the Monte Carlo Markov Chain procedure, with 30 000 burn-in followed by 150 000 MCMC repetitions.
Exact test of population differentiation has been carried out using GENEPOP, and the significance levels were assessed by Markov chain procedure.
In a chained procedure, the health state of interest is not directly compared with death but indirectly with the aid of an intermediate anchor health state [ 27- 29].
A limitation is that a chained procedure is more complex, because it adds an additional step to the valuation process, possibly leading to extra noise [ 28].
To account for missing data we performed multiple imputation using the mi impute chained procedure in Stata 12, which uses an iterative multivariable regression procedure to generate distributions for each variable with missing data that are conditional on all other variables in the imputation models [ 33].
