Michael A. Martin

The transformational dimension in the realization of business value from information technology

Econometric studies have highlighted factors that appear to explain the differential effects of information technology (IT) on productivity at the firm level. Central to these explanations is the concept of organizational transformation; that value realization from IT depends on time-consuming investments in organizational change and results in new, often intangible, organizational assets. The aim of this study was to further investigate the concept of IT-enabled organizational transformation as a component of the value realized from IT at the firm level. Survey data was analyzed from respondents from 1050 businesses of varying sizes and across industries. Transformational benefits were found to exist as a distinct benefit category and to be closely related to other forms of IT-generated business benefits. They were also an important component of overall IT business value. Qualitative data illustrated these findings and pointed to possible complex causal relationships in the generation of IT value. The findings have implications for models of IT business value generation and for managerial practice.

On Bootstrap Iteration for Coverage Correction in Confidence Intervals

Abstract Iterated bootstrap procedures may be used to reduce error in many statistical problems. We discuss their use in constructing confidence intervals with accurate coverage and show that bootstrap coverage correction produces improvements in coverage accuracy of order n −1/2 in one-sided intervals, but of order n −1 in two-sided intervals. Explicit formulas are provided for the dominant term in coverage error after iteration in each case. These results are used to compare various iterated bootstrap intervals and to assess the effect of bootstrap iteration on other indicators of interval performance, such as position of critical points and length of interval. We show that, for one-sided intervals, the coverage-correction algorithm yields critical points that are second-order correct. This is not the case for two-sided intervals, where second-order correctness is not crucial in obtaining high-order coverage accuracy. We also show that the asymptotic mean increase in length between the original and cove...

On Local Smoothing of Nonparametric Curve Estimators

Abstract We develop new local versions of familiar smoothing methods, such as cross-validation and smoothed cross-validation, in the contexts of density estimation and regression. These new methods are locally adaptive in the sense that they capture smooth local fluctuations in the curve by using smoothly varying bandwidths that change as the character of the curve changes. Moreover, the new methods are accurate, easy to apply, and computationally expedient.

Exact convergence rate of bootstrap quantile variance estimator

SummaryIt is shown that the relative error of the bootstrap quantile variance estimator is of precise order n-1/4, when n denotes sample size. Likewise, the error of the bootstrap sparsity function estimator is of precise order n-1/4. Therefore as point estimators these estimators converge more slowly than the Bloch-Gastwirth estimator and kernel estimators, which typically have smaller error of order at most n-2/5.

A randomised control trial of short term efficacy of in-shoe foot orthoses compared with a wait and see policy for anterior knee pain and the role of foot mobility

Objectives To investigate the short-term clinical efficacy of in-shoe foot orthoses over a wait-and-see policy in the treatment of anterior knee pain (AKP) and evaluate the ability of foot posture measures to predict outcome. Design Single-blind, randomised control trial. Participants Forty participants (18–40 years) with clinically diagnosed AKP of greater than 6-week duration, who had not been treated with orthoses in the previous 5 years. Intervention Prefabricated orthoses perceived as most comfortable from a selection of 3 different hardness values compared with a wait-and-see control group. Outcome measures Participant-perceived global improvement, Kujala Patellofemoral Score, usual and worst pain severity over the previous week and the Patient Specific Functional Scale measures at 6 weeks. Results Foot orthoses produced a significant global improvement compared with the control group (p = 0.008, relative risk reduction = 8.47%, numbers needed to treat = 2). Significant differences also occurred in measures of function (standardised mean difference = 0.71). Within the intervention group, individuals who exhibited a change in midfoot width from weight bearing to non-weight bearing of >11.25 mm were more likely to report a successful outcome (correct classification 77.8%). Conclusion This is the first study to show orthoses provide greater improvements in AKP than a wait-and-see approach. Individuals with greater midfoot mobility are more likely to experience success from treatment. Trial Registration ACTRN12611000492954

Bootstrap hypothesis testing for some common statistical problems: A critical evaluation of size and power properties

The construction of bootstrap hypothesis tests can differ from that of bootstrap confidence intervals because of the need to generate the bootstrap distribution of test statistics under a specific null hypothesis. Similarly, bootstrap power calculations rely on resampling being carried out under specific alternatives. We describe and develop null and alternative resampling schemes for common scenarios, constructing bootstrap tests for the correlation coefficient, variance, and regression/ANOVA models. Bootstrap power calculations for these scenarios are described. In some cases, null-resampling bootstrap tests are equivalent to tests based on appropriately constructed bootstrap confidence intervals. In other cases, particularly those for which simple percentile-method bootstrap intervals are in routine use such as the correlation coefficient, null-resampling tests differ from interval-based tests. We critically assess the performance of bootstrap tests, examining size and power properties of the tests numerically using both real and simulated data. Where they differ from tests based on bootstrap confidence intervals, null-resampling tests have reasonable size properties, outperforming tests based on bootstrapping without regard to the null hypothesis. The bootstrap tests also have reasonable power properties.

Analyzing Ordinal Scales in Studies of Virtual Environments: Likert or Lump It!

Likert scaled data, which are frequently collected in studies of interaction in virtual environments, demand specialized statistical tools for analysis. The routine use of statistical methods appropriate for continuous data in this context can lead to significant inferential flaws. Likert scaled data are ordinal rather than interval scaled and need to be analyzed using rank based statistical procedures that are widely available. Likert scores are lumpy in the sense that they cluster around a small number of fixed values. This lumpiness is made worse by the tendency for subjects to cluster towards either the middle or the extremes of the scale. We suggest an ad hoc method to deal with such data which can involve a further lumping of the results followed by the application of nonparametric statistics. Averaging Likert scores over several different survey questions, which is sometimes done in studies of interaction in virtual environments, results in a different sort of lumpiness. The lumped variables which are obtained in this manner can be quite murky and should be used with great caution, if at all, particularly if the number of questions over which such averaging is carried out is small.

Better nonparametric bootstrap confidence intervals for the correlation coefficient

We respond to criticism leveled at bootstrap confidence intervals for the correlation coefficient by recent authors by arguing that in the correlation coefficient case, non–standard methods should be employed. We propose two such methods. The first is a bootstrap coverage coorection algorithm using iterated bootstrap techniques (Hall, 1986; Beran, 1987a; Hall and Martin, 1988) applied to ordinary percentile–method intervals (Efron, 1979), giving intervals with high coverage accuracy and stable lengths and endpoints. The simulation study carried out for this method gives results for sample sizes 8, 10, and 12 in three parent populations. The second technique involves the construction of percentile–t bootstrap confidence intervals for a transformed correlation coefficient, followed by an inversion of the transformation, to obtain “transformed percentile–t” intervals for the correlation coefficient. In particular, Fishers z–transformation is used, and nonparametric delta method and jackknife variance estima...

Using supervised principal components analysis to assess multiple pollutant effects

Background Many investigations of the adverse health effects of multiple air pollutants analyze the time series involved by simultaneously entering the multiple pollutants into a Poisson log-linear model. This method can yield unstable parameter estimates when the pollutants involved suffer high intercorrelation; therefore, traditional approaches to dealing with multicollinearity, such as principal component analysis (PCA), have been promoted in this context. Objectives A characteristic of PCA is that its construction does not consider the relationship between the covariates and the adverse health outcomes. A refined version of PCA, supervised principal components analysis (SPCA), is proposed that specifically addresses this issue. Methods Models controlling for long-term trends and weather effects were used in conjunction with each SPCA and PCA to estimate the association between multiple air pollutants and mortality for U.S. cities. The methods were compared further via a simulation study. Results Simulation studies demonstrated that SPCA, unlike PCA, was successful in identifying the correct subset of multiple pollutants associated with mortality. Because of this property, SPCA and PCA returned different estimates for the relationship between air pollution and mortality. Conclusions Although a number of methods for assessing the effects of multiple pollutants have been proposed, such methods can falter in the presence of high correlation among pollutants. Both PCA and SPCA address this issue. By allowing the exclusion of pollutants that are not associated with the adverse health outcomes from the mixture of pollutants selected, SPCA offers a critical improvement over PCA.

Breast-Conserving Surgery Versus Mastectomy for Survival from Breast Cancer: the Western Australian Experience

The focus of this study was the relative survival rates of breast cancer patients whose treatment was breast-conserving surgery compared with that of mastectomy, adjusting for tumor size and nodal status because these factors may be intrinsically associated with mastectomy being the treatment of choice. Patient age was also accounted for in the model. By adjusting for these factors, we mitigate them as confounders of treatment choice in assessing effects on survival rates. Data were sourced from linked administrative data from the Western Australian Department of Health Record Linkage Unit. The data consisted of linked records containing the diagnosis, subsequent hospital admission, and death records of about 3000 women diagnosed with cancer in Western Australia between 1 January 1995 and 31 December 1999. Cox proportional hazards regression was used to investigate survival outcomes of breast-conserving surgery compared with that of mastectomy, adjusting for tumor size, nodal status, and subject age. The hazard of death is reduced by a factor of about one half for subjects whose treatment was breast-conserving surgery over treatment by mastectomy. Furthermore, the hazard of death increases substantially for subjects with nodal involvement over subjects for whom there has been no identified spread to regional lymph nodes. Hazard of death increases as both age and tumor size increase. Western Australian breast cancer patients treated with breast-conserving surgery have improved survival outcomes over those treated with mastectomy, after allowing for tumor size, patient age, and lymph node involvement.