Bias treatment

There exist two different techniques to control for common methods bias Choice of study design and statistical procedures (Podsakoff et al. 2003). 

In relation to the design of the study, most of the questions asked were at a rather concrete level and included Issues like product use, product adaption, and lead userness. There were no constructs involving high levels of abstraction like innate attitudes. Use of more concrete constructs alleviates common source variance, as they are easier to measure (Cote and Buckley 1987 Malhotra et al. 2006). I focused to employ clear language, relying on measurement scales that have already been established in research. Different anchoring points of scales were used, and total anonjmiity was warranted to respondents (Podsakoff etal. 2003). 

The statistical controls for common method bias were only carried out for the full (mediated) model, as the indicators for all constructs were obtained from the same source. Three statistical remedies were used First, Harman s single factor test was employed. 1 applied factor analysis without rotation to check for the fit of a single factor model. The variance extracted for a one factor solution was below 50% (35,05%). With eigenvalues 1, six factors were extracted. Thus one can conclude that there is no single 

Pull model with latent enminno method variance factor 

Construct Indicator indicator T-value indicator T-value Ac factor T-value Am  

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For comparison purposes, plant data and reconciled data, both with and without bias treatment, over the whole operating cycle of the pyrolysis reactor for some variables are plotted in Fig. 8. This figure clearly shows that the measurements obtained from coil 2 are biased. There were not many differences between measured and reconciled values for the other variables. 

Reaction gas (seem) Bias treatment (001) Fast growth (111) Fast growth... 

The core of the nucleation model proposed in Refs. [362, 363] is an assumption based on the experimental data that epitaxially oriented nucleation sites are formed in the SiC layer of about 10-nm thickness during the bias treatment. These sites are exposed at the SiC surface, while plasma etching of SiC is occurring during both the BEN treatment and the successive diamond growth process. The model of nucleation process is schematically depicted in Figure 11.57 ... 

Introduced successfully for tires in 1967, glass fibers had properties that made them very attractive for use in tires (5,8). The britdeness of glass fibers, however, imposed some limitations on the final tine cord properties because of the requirement that each fiber be individually coated with a mbbery adhesive to avoid interfilament damage during fabrication and use. This additional treatment step is introduced at the fiber manufacturing stage. For several years fiber glass was used extensively in bias-belted and radial tires, but was ultimately replaced by steel belts in radial tires. 

This is a formidable analysis problem. The number and impact of uncertainties makes normal pant-performance analysis difficult. Despite their limitations, however, the measurements must be used to understand the internal process. The measurements have hmited quahty, and they are sparse, suboptimal, and biased. The statistical distributions are unknown. Treatment methods may add bias to the conclusions. The result is the potential for many interpretations to describe the measurements equaUv well. 

Clinical trials should be designed so as to mirtimise potential sources of bias. It is known that patients can demonstrate a positive response to treatments that they believe will benefit them, even if no pharmaceutical agent has been admrrtistered (the placebo effect ). Similarly, investigators may be biased in their observations by an expectation of particular results. To avoid such bias, blinded trial designs are used. 

Scheme 37 shows a reaction sequence leading to a mono(amidinato) indium bia(arylimido) complex. Subsequent treatment of the latter with Ti(NMe2)4 resulted in formation of the heterobimetallic In/Ti complex [But(NPr )2]In /t-NCgH3Pri-2,6 2Ti(NMe2)2 (cf. Sections 111.B.2 and V.A.l)." ... 

Bemabeu-Gonzalvez A., Pastor-Bias M.M., and Martm-Martmez J.M., 1998, Modified adhesion of rubber materials by surface migration of wax and zinc stearate, in Proceedings of the World Polymer Congress, 37th International Symposium on Macromolecules MACRO 98, Gold Coast, Australia, 705. Romero-Sanchez M.D., Pastor-Bias M.M., and Martm-Martmez J.M., 2001, Adhesion improvement of SBR rubber by treatment with trichloroisocyanuric acid solutions in different esters, Int. J. Adhes. Adhes., 21, 325-337. 

Cepeda-Jimenez C.M., Pastor-Bias M.M., Martln-Martmez J.M., and Gottschalk P., 2002, A new water-based chemical treatment based on sodium dichloroisocyanurate (DCI) for rubber soles in footwear industry, J. Adhes. Sci Technol, 16(3), 257-284. 

Romero-Sanchez M.D., Pastor-Bias M.M., and Martm-Martmez J.M., 2003, Treatment of a styrene-butadiene-styrene rubber with corona discharge to improve the adhesion to polyurethane adhesive, Int. J. Adhes. Adhes, 23(1), 49-57. 

Ortiz-Magan A.B., Pastor-Bias M.M., Eerrandiz-Gomez T.P., Morant-Zacares C., and Martfn-Martfnez J.M., 2001, Surface modifications produced by N2 and O2 RF-plasma treatment on a synthetic vulcanised rubber. Plasmas Polym., 6(1,2), 81-105. 

Pastor-Sempere N., Eemandez-Garcfa J.C., Orgiles-Barcelo A.C., Pastor-Bias M.M., Martfn-Martfnez J.M., and Dillard J.G., 1998, Surface treatment of styrene-butadiene rubber with carboxylic acid, in First International Congress on Adhesion Science and Technology, W.J. van Ooij and H.R. Anderson Jr. (Eds), Utrecht, VSP, 461 94. 

Each of the analyses reported outcomes for patients responding to and continuing treatment after the original 6-week clinical trial that is, after the exclusion of patients withdrawing from the original trial for whatever reason (e.g. poor tolerability, lack of response). This probably introduced bias in favour of haloperidol, since there were significantly more responders to olanzapine. 

Randomized, controlled clinical trials reduce bias and variability by a process of selection, randomization and standardization of treatment, and often take place under artificial conditions isolated from those of routine clinical practice (Freemande et al, 1993 Simon et al, 1995b). Yet it is the uncontrolled interactions of a dmg technology with patients, health-care workers and the system of health care that ultimately lead to much of the variability in outcomes and expenditures in clinical practice. Thus the value of RCTs in evaluating cost-effectiveness in clinical practice maybe limited (Reeder, 1995 Simon et al, 1995b Hotopf et al, 1996). 

Differences exist in primary care between the patterns of prescribing fluoxetine, paroxetine or sertraline, which may influence cost outcomes. Sertraline-treated patients are more likely to have their dose increased (Sclar et al, 1995 Donoghue, 1998), and to drop out of treatment prematurely (Donoghue, 1998). The apparent need to titrate doses upwards with sertraline may require more involvement by the clinician and may delay response to treatment, with resultant increases in direct health costs (Sclar et al, 1995). However, these economic findings are retrospective, may suffer from selection bias, and being derived from HMO patients may not be generalizable to other populations confirmation in further studies is required. 

Randomization refers to the process of assigning subjects by chance to treatments. This eliminates known and unknown sources of bias that could interfere with accurate interpretation of the study results. The main problem that randomization is intended to prevent is bias in subject selection. Without randomization, investigators might consciously or subconsciously select subjects to receive the active treatment, which, they believe, are most likely to respond. History shows that uncontrolled studies are much more likely to provide exaggerated support in favor of the effectiveness of a treatment than properly controlled trials (Pocock, 1983). Therefore, whenever possible, randomization should be used in order to help insure a fair and unbiased evaluation of the intervention under study. 

In addition to randomization, blinding and placebo controls are safeguards often used to insure that the results obtained are not subject to bias or confounding. Blinding refers to methods used to keep subjects and/or investigators unaware of which treatment a subject is receiving in a clinical... 

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