Internal validation

In order to assure the internal validity of the data analysis, two of the authors (RJ and PF) analysed the original case studies (that are written in Portuguese) independently. The results were compared and at r disagreement was discussed and resolved. Then all the relevant evidence was translated into English to be discussed with the third author (JG). 

Weinberg S, Romoff RM, Stein GC. Handbook of System Validation. Weinberg, Spelton and Sax Inc. 1993 Weinberg S. Validation Compliance Annual, in Weinberg S, Editor, International Validation Forum. Marcel Dekker New York, 1995. 

To be useful to those concerned with choices in the allocation of health and social care resources, the data for economic evaluations need to be timely, relevant, credible and accurate (Davies, 1998). As a minimum, the costs associated with the interventions should be estimated from activity data, which quantify resources used, and price or unit cost data. Often evidence from well-controlled prospective trials with high internal validity is required to establish whether differences in economic end points are directly attributable to the interventions. However, the economic evaluations of acetylcholinesterase inhibitors estimated costs from retrospective analysis of available datasets Qonsson et al, 1999b), analysis of published literature (e.g. Stewart et al, 1998) and expert opinion (e.g. O Brien et al, 1999 Neumann et al, 1999). This means that it is not clear whether differences in costs were due to the anticholinesterase inhibitors or to other factors such as availability of services in different areas, the living situation of the patient, or disease severity. 

The many solutions that have been proposed thus far have been reviewed recently by Deane [40]. Some empirical methods of validation are also discussed in Chapter 36. In this section we only discuss three representative approaches, i.e. empirical, statistical and by internal validation. (There are several variants of these approaches which we cannot discuss here.) It is not always clear which method should be preferred under given circumstances [37]. It may be useful to apply... 

The method of cross-validation is based on internal validation, which means that one predicts each element in the data set from the results of an analysis of the remaining ones. This can be done by leaving out each element in turn, which in the case of an nxp table would require nxp analyses. Wold [44] has implemented a scheme for leaving out groups of elements at the same time, which reduces the... 

Yin (Yin, 1994) discusses four criteria forjudging the quality of the research design. After the external validity as already discussed, Yin defines the construct validity, the reliability, and the internal validity. The construct validity is the validity of the operational measures used for the research concepts. In this study construct validity will be addressed by the use of multiple sources for data collection. Case histories,... 

Recently, a standardized protocol for using the guinea pig for phototoxicity testing has been proposed (Nilsson et al., 1993), which has been the subject of an international validation exercise. This is detailed below in Figure 11.3. 

Figure 9 Observed data (amount absorbed in vivo vs. amount released in vitro) for the five ISMN test formulations included in IVIVC development and internal validation. The fitted IVIVC equations are shown as well as the corresponding predicted lines. Panel a shows the analysis where the study-specific reference was used for deconvolution and panel b where the reference for Study 194.573 was used for the deconvolution analysis of all study data.

Internal validity of the rodent models involves verifying that withdrawal severity (indicated by numbers of observed behavioral changes) reflects chronic nicotine exposnre followed by termination of that exposure. The rat model involving continnons nicotine infusion has probably been the most extensively validated in this sense (Malin 2001), meeting the following validity criteria ... 

Unlike test set validation methods, cross-validation methods attempt to validate a model using the calibration data only, without requiring the preparation and analysis of an additional test set of samples. This involves the execution of one or more internal validation procedures (hereby called subvalidations), where each subvalidation involves three steps ... 

Monitoring the MMA/DMAAm reaction is challenging becanse both monomers have very similar NIR spectra, and because other interfering snbstances are present in the reaction mixtnre. The anthors prepared calibration samples gravimetrically and made the NIR measurements at reaction temperatnres. The calibration sets consisted of only five or six samples, which is considerably fewer than standard recommendations for NIR chemometric model development. The final models for MMA and DMAAm were validated with an internal validation set as well as an external reaction validation. The performance of the models is summarized in Table 15.6. This table inclndes a measurement of the standard deviation of an external GC method... 

Monomer RMSEC (mol/L) RMSEP (mol/L) internal validation RMSEP (mol/L) external validation GC STD (mol/L)... 

REDIFEM—This fire model has applications including steady state releases of compressible gas/vapor, incompressible liquid and transient release from a gas vessel, Gaussian Plume models, continuous free momentum, BLEVE, and confined and unconfined vapor cloud explosions. REDIEEM is reported to have internal validation with ISO 9001 and checked against PHAST and ERED. 

Placebo-controlled trial of a new active medicinal product, if positive, means that the trial was capable of detecting a difference, and that the test treatment is, at least, more efficacious than placebo. This achieves two outcomes provision of an internal validity check of the trial methods, and provision to regulatory authorities of a basis on which to judge the difference between a statistically significant but clinically inadequate effect that would probably lead to the drug not being licensed. 

Perhaps due to lack of regulation, no official, harmonized or internationally validated method is available at present. Despite lack of official standards, many protocols of Protected Denomination of Origin list limits for total polyphenols and this data is often nsed in trade. 

Root Mean Square Error of Prediction (RMSEP) Plot (Model Diagnostic) Prediction error is a useful metric for selecting the optimum number of factors to include in the model. This is because the models are most often used to predict the concentrations in future unknown samples. There are two approaches for generating a validation set for estimating the prediction error internal validation (i.e., cross-validation with the calibration data), or external validation (i.e., perform prediction on a separate validation set). Samples are usually at a premium, and so we most often use a cross- validation approach. 

Genschow E, Spiehnann H, Scholz G et al (2002) The ECVAM international validation study on in vitro embryotoxicity tests results of the definitive phase and evaluation of prediction models. European Centre for the Validation of Alternative Methods. Altern Lab Anim 30(2) 151-176... 

The internal validity. There should be no indications of a potential bias... 

One of the more common criticisms of an evidence-based approach to clinical practice is that clinical trials and clinical practice are only weakly related. In research language, the external validity of many efficacy studies is suspect. External validity, which refers to the extent to which the results of the research are gener-alizable to clinical populations, is often contrasted to internal validity, i.e., the extent to which a study is methodologically sound. Without internal validity, it is hard to argue for the external validity of a study. Many internally valid studies are not fully relevant to clinical... 

Maier, W., Philipp, M., Heuser, I., et al. Improving depression severity assessment - I. Reliability, internal validity and sensitivity to change of three observer depression scales. J. Psvchiatr. Res. 22, 3-12. 1988. 

The added value of single-laboratory validation is that it simplifies the next step—interlaboratory validation—and thereby minimizes the gap between internally (validated or not) developed methods and the status of interlaboratory validation. By optimizing the method first within the laboratory, as a kind of preliminary work, an enormous amount of collaborators time and money is saved [58]. 

At this point, we have the data generated by our potentiometric sensor array inserted in EasyNN. The next step to follow is to select the training, internal validation and test subsets. To do so, click /Edit/ Change Range of Types... and a window appears in which the fraction of samples for each task can be selected. 

In the next window, write from what sample and how many of them do you want to assign as Training and press OK. Repeat the process to select the internal Validation samples and the test samples (Query). It may be observed in the spreadsheet how the training samples are highlighted in blue, how the internal validation samples are highlighted in green and the test ones in red. 

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