Differential gains from Business Link support and advice:a treatment effects approach

The provision of advisory support to small firms is almost ubiquitous in OECD countries, although it is organised in different ways and is justified on slightly different grounds. In England publicly supported advisory services are provided through the Business Link (BL) network. Here, we consider two questions: what sort of companies receive advisory support from BL; and, what types of firms benefit most from that support? Our analysis is based on a telephone survey of 2000 firms, around half of which had received intensive assistance from BL between April and October 2003. Probit analysis suggests that the probability of receiving assistance was greater among younger businesses, those with larger numbers of directors in the firm, and those with more gender diversity among the firm's leadership team. Our business-growth models suggest that BL intensive assistance was having a positive effect on employment growth in 2003. BL had a positive but insignificant impact on sales growth over the period. Employment growth effects tend to be larger where firms have a management and organisational structure, which is more conducive to absorbing and making use of external advice. The analysis suggests that BL might increase its impact through targeting these larger, more export-orientated, businesses. Employment growth effects differ little, however, depending on either the ethnic or the gender diversity of the leadership team.

Statnote 5: Is one set of data more variable than another?

There may be circumstances where it is necessary for microbiologists to compare variances rather than means, e,g., in analysing data from experiments to determine whether a particular treatment alters the degree of variability or testing the assumption of homogeneity of variance prior to other statistical tests. All of the tests described in this Statnote have their limitations. Bartlett’s test may be too sensitive but Levene’s and the Brown-Forsythe tests also have problems. We would recommend the use of the variance-ratio test to compare two variances and the careful application of Bartlett’s test if there are more than two groups. Considering that these tests are not particularly robust, it should be remembered that the homogeneity of variance assumption is usually the least important of those considered when carrying out an ANOVA. If there is concern about this assumption and especially if the other assumptions of the analysis are also not likely to be met, e.g., lack of normality or non additivity of treatment effects then it may be better either to transform the data or to carry out a non-parametric test on the data.

Statnote 11: the two-factor analysis of variance

Experiments combining different groups or factors are a powerful method of investigation in applied microbiology. ANOVA enables not only the effect of individual factors to be estimated but also their interactions; information which cannot be obtained readily when factors are investigated separately. In addition, combining different treatments or factors in a single experiment is more efficient and often reduces the number of replications required to estimate treatment effects adequately. Because of the treatment combinations used in a factorial experiment, the degrees of freedom (DF) of the error term in the ANOVA is a more important indicator of the ‘power’ of the experiment than simply the number of replicates. A good method is to ensure, where possible, that sufficient replication is present to achieve 15 DF for each error term of the ANOVA. Finally, in a factorial experiment, it is important to define the design of the experiment in detail because this determines the appropriate type of ANOVA. We will discuss some of the common variations of factorial ANOVA in future statnotes. If there is doubt about which ANOVA to use, the researcher should seek advice from a statistician with experience of research in applied microbiology.

Statnote 13: a more complex analysis of variance incorporating a 'repeated measures' factor

Experiments combining different groups or factors and which use ANOVA are a powerful method of investigation in applied microbiology. ANOVA enables not only the effect of individual factors to be estimated but also their interactions; information which cannot be obtained readily when factors are investigated separately. In addition, combining different treatments or factors in a single experiment is more efficient and often reduces the sample size required to estimate treatment effects adequately. Because of the treatment combinations used in a factorial experiment, the degrees of freedom (DF) of the error term in the ANOVA is a more important indicator of the ‘power’ of the experiment than the number of replicates. A good method is to ensure, where possible, that sufficient replication is present to achieve 15 DF for the error term of the ANOVA testing effects of particular interest. Finally, it is important to always consider the design of the experiment because this determines the appropriate ANOVA to use. Hence, it is necessary to be able to identify the different forms of ANOVA appropriate to different experimental designs and to recognise when a design is a split-plot or incorporates a repeated measure. If there is any doubt about which ANOVA to use in a specific circumstance, the researcher should seek advice from a statistician with experience of research in applied microbiology.

The use of analysis of variance (ANOVA) in applied microbiology

Experiments combining different groups or factors and which use ANOVA are a powerful method of investigation in applied microbiology. ANOVA enables not only the effect of individual factors to be estimated but also their interactions; information which cannot be obtained readily when factors are investigated separately. In addition, combining different treatments or factors in a single experiment is more efficient and often reduces the number of replications required to estimate treatment effects adequately. Because of the treatment combinations used in a factorial experiment, the DF of the error term in the ANOVA is a more important indicator of the ‘power’ of the experiment than the number of replicates. A good method is to ensure, where possible, that sufficient replication is present to achieve 15 DF for each error term of the ANOVA. Finally, it is important to consider the design of the experiment because this determines the appropriate ANOVA to use. Some of the most common experimental designs used in the biosciences and their relevant ANOVAs are discussed by. If there is doubt about which ANOVA to use, the researcher should seek advice from a statistician with experience of research in applied microbiology.

Quantitative assessment of the pharmacotherapy of biopolar disorder and schizophrenia

The work present in this thesis was aimed at assessing the efficacy of lithium in the acute treatment of mania and for the prophylaxis of bipolar disorder, and investigating the value of plasma haloperidol concentration for predicting response to treatment in schizophrenia. The pharmacogenetics of psychotropic drugs is critically appraised to provide insights into interindividual variability in response to pharmacotherapy, In clinical trials of acute mania, a number of measures have been used to assess the severity of illness and its response to treatment. Rating instruments need to be validated in order for a clinical study to provide reliable and meaningful estimates of treatment effects, Eight symptom-rating scales were identified and critically assessed, The Mania Rating Scale (MRS) was the most commonly used for assessing treatment response, The advantage of the MRS is that there is a relatively extensive database of studies based on it and this will no doubt ensure that it remains a gold standard for the foreseeable future. Other useful rating scales are available for measuring mania but further cross-validation and validation against clinically meaningful global changes are required. A total of 658 patients from 12 trials were included in an evaluation of the efficacy of lithium in the treatment of acute mania. Treatment periods ranged from 3 to 4 weeks. Efficacy was estimated using (i) the differences in the reduction in mania severity scores, and (ii) the ratio and difference in improvement response rates. The response rate ratio for lithium against placebo was 1.95 (95% CI 1.17 to 3.23). The mean number needed to treat was 5 (95% CI 3 to 20). Patients were twice as likely to obtain remission with lithium than with chlorpromazine (rate ratio = 1.96, 95% CI 1.02 to 3.77). The mean number needed to treat (NNT) was 4 (95% CI 3 to 9). Neither carbamazepine nor valproate was more effective than lithium. The response rate ratios were 1.01 (95% CI 0.54 to 1.88) for lithium compared to carbarnazepine and 1.22 (95% CI 0.91 to 1.64) for lithium against valproate. Haloperidol was no better than lithium on the basis of improvement based on assessment of global severity. The differences in effects between lithium and risperidone were -2.79 (95% CI -4.22 to -1.36) in favour of risperidone with respect to symptom severity improvement and -0.76 (95% CI -1.11 to -0,41) on the basis of reduction in global severity of disease. Symptom and global severity was at least as well controlIed with lithium as with verapamil. Lithium caused more side-effects than placebo and verapamil, but no more than carbamazepine or valproate. A total of 554 patients from 13 trials were included in the statistical analysis of lithium's efficacy in the prophylaxis of bipolar disorder. The mean follow-up period was 5-34 months. The relapse risk ratio for lithium versus placebo was 0.47 (95% CI 0.26 to 0.86) and the NNT was 3 (95% CI 2 to 7). The relapse risk ratio for lithium versus imipramine was 0.62 (95% CI 0.46 to 0.84) and the NNT was 4 (951% Cl 3 to 7), The combination of lithium and imipramine was no more effective than lithium alone. The risk of relapse was greater with lithium alone than with the lithium-divalproate combination. A risk difference of 0.60 (95% CI 0.21 to 0.99) and an NNT of 2 (95% CI 1 to 5) were obtained. Lithium was as effective as carbamazepine. Based on individual data concerning plasma haloperidol concentration and percent improvement in psychotic symptoms, our results suggest an acceptable concentration range of 11.20-30.30 ng/mL A minimum of 2 weeks should be allowed before evaluating therapeutic response. Monitoring of drug plasma levels seems not to be necessary unless behavioural toxicity or noncompliance is suspected. Pharmacokinetics and pharmacodynamics, which are mainly determined by genetic factors, contribute to interindividual and interethnic variations in clinical response to drugs. These variations are primarily due to differences in drug metabolism. Variability in pharmacokinetics of a number of drugs is associated with oxidation polymorphism. Debrisoquine/sparteine hydroxylase (CYP2D6) and the S-mephenytoin hydroxylase (CYP2C19) are polymorphic P450 enzymes with particular importance in psychopharmacotherapy. The enzymes are responsible for the metabolism of many commonly used antipsychotic and antidepressant drugs. The incidence of poor metabolisers of debrisoquine and S-mephenytoin varies widely among populations. Ethnic variations in polymorphic isoenzymes may, at least in part, explain ethnic differences in response to pharmacotherapy of antipsychotics and antidepressant drugs.

Accommodation in young adults wearing multifocal soft contact lenses under long- and short- wavelength lighting

Purpose: Several studies have suggested accommodative lags may serve as a stimulus for myopic growth, and while a blurred foveal image is believed to the main stimulus for accommodation, spectral composition of the retinal image is also believed to influence accommodative accuracy. Of particular interest is how altering spectral lighting conditions influences accommodation in the presence of soft multifocal contact lenses, which are currently being used off-label for myopia control. Methods: Accommodative responses were assessed using a Grand Seiko WAM-5500 autorefractor for four target distances: 25, 33, 50, and 100cm for 30 young adult subjects (14 myopic, 16 emmetropic; mean refractive errors (±SD, D) -4.22±2.04 and -0.15±0.67 respectively). Measurements were obtained with four different soft contact lenses, Single vision distance (SVD), Single vision near (SVN), Centre-Near (CN) and Centre-Distance (CD) (+1.50 add), and three different lighting conditions: red (peak λ 632nm), blue (peak λ 460nm), and white (peak λ 560nm). Corrections for chromatic differences in refraction were made prior to calculating accommodative errors. Results: The size of accommodative errors was significantly affected by lens design (p<0.001), lighting (p=0.027), and target distance (p=0.009). Mean accommodative errors were significantly larger with the SV lenses compared to the CD and CN designs (p<0.001). Errors were also significantly larger under blue light compared to white (p=0.004) and a significant interaction noted between lens design and lighting (p<0.001). Blue light generally decreased accommodative lags and increased accommodative leads relative to white and red light, the opposite was true of red light (p≤0.001). Lens design also significantly influenced direction of accommodative error (i.e. lag or lead) (p<0.001). Interactions with or between refractive groups were not found to be statistically significant for either the magnitude or direction of accommodative error (p>0.05 for all). Conclusions: Accuracy of accommodation is affected by both lens design and by wavelength of lighting. These accommodative lag data lend some support to recent speculation about the potential therapeutic value of lighting with a spectral bias towards blue during near work for myopia, although such treatment effects are likely to be more subtle under broad compared to the narrow spectrum lighting conditions used here.

Comparing methods to separate treatment from self-selection effects in an online banking setting

The literature discusses several methods to control for self-selection effects but provides little guidance on which method to use in a setting with a limited number of variables. The authors theoretically compare and empirically assess the performance of different matching methods and instrumental variable and control function methods in this type of setting by investigating the effect of online banking on product usage. Hybrid matching in combination with the Gaussian kernel algorithm outperforms the other methods with respect to predictive validity. The empirical finding of large self-selection effects indicates the importance of controlling for these effects when assessing the effectiveness of marketing activities.

Spillover effects of service failures in coalition loyalty programs:the buffering effect of special treatment benefits

Coalition loyalty programs are on the rise, yet few studies investigate the impact of service failures in such programs. Using data from a retail context, the authors show that a program partner deemed responsible for a service failure suffers negative customer responses. However, customers' perceptions of the benefits of the coalition loyalty program buffer these consequences. Perhaps most importantly, when customers perceive the program's special treatment benefits as low, direct and indirect spillover effects occur, such that a service failure by one program partner has a negative effect on customer loyalty toward the program itself. © 2013 New York University.

Fatigue behaviour of C-Mn-B steels:effects of heat treatment prestrain and residual stress

The fatigue-crack propagation and threshold behaviour of a C-Mn steel containing boron has been investigated at a range of strength levels suitable for mining chain applications. The heat-treatment variables examined include two austenitizing temperatures (900 degree C and 1250 degree C) and a range of tempering treatments from the as-quenched condition to tempering at 400 degree C. In mining applications the haulage chains undergo a 'calibration' process which has the effect of imposing a tensile prestrain on the chain links before they go into service. Prestrain is shown to reduce threshold values in these steels and this behaviour is related to its effects on the residual stress distribution in the test specimens.