Generating best evidence from qualitative research: the role of data analysis

Objective: To outline the importance of the clarity of data analysis in the doing and reporting of interview-based qualitative research.

Approach: We explore the clear links between data analysis and evidence. We argue that transparency in the data analysis process is integral to determining the evidence that is generated. Data analysis must occur concurrently with data collection and comprises an ongoing process of 'testing the fit' between the data collected and analysis. We discuss four steps in the process of thematic data analysis: immersion, coding, categorising and generation of themes.

Conclusion: Rigorous and systematic analysis of qualitative data is integral to the production of high-quality research. Studies that give an explicit account of the data analysis process provide insights into how conclusions are reached while studies that explain themes anchored to data and theory produce the strongest evidence.

Interactive dance performance : movement data and the 'materiality' of the system

This paper describes a recent performance work I made using dance and live feed video
processing, 1 + x: mid-range projections, commissioned by the Seoul Contemporary Dance
Company and first performed in Melbourne in July 2005. This work forms a basis for discussing
my interest in creating performance images that reveal 'interiority'. I am interested in how you
embed the 'feel' of the human systematically in an interactive structure, and how that process
can produce a poetic that arises from the detailed and nuanced play between real and virtual
images on the same screen. How do you abstract and play with a performer's movement, play
with it in real and virtual time, so that it gives the work an emotional charge? Its like playing with
the process of 'becoming virtual' - and I'm being deliberately Deleuzian about that - how do you
'become virtual' in the sense of melding performer and image so that the meaning exists
between - in the connection between the two?

This quest to get the energy, the 'lived', 'felt' quality of the movement into the imagery gives rise
to research questions about how 'presence' is perceived in movement. What elements of the
raw movement data do you need to keep and what can you throwaway, and still keep the
personality, the emotion, the 'life' of that movement? How do you make a virtual, interactive
performance system that has its own 'materiality'?

A clustering based hybrid system for mass spectrometry data analysis

Recently, much attention has been given to the mass spectrometry (MS) technology based disease classification, diagnosis, and protein-based biomarker identification. Similar to microarray based investigation, proteomic data generated by such kind of high-throughput experiments are often with high feature-to-sample ratio. Moreover, biological information and pattern are compounded with data noise, redundancy and outliers. Thus, the development of algorithms and procedures for the analysis and interpretation of such kind of data is of paramount importance. In this paper, we propose a hybrid system for analyzing such high dimensional data. The proposed method uses the k-mean clustering algorithm based feature extraction and selection procedure to bridge the filter selection and wrapper selection methods. The potential informative mass/charge (m/z) markers selected by filters are subject to the k-mean clustering algorithm for correlation and redundancy reduction, and a multi-objective Genetic Algorithm selector is then employed to identify discriminative m/z markers generated by k-mean clustering algorithm. Experimental results obtained by using the proposed method indicate that it is suitable for m/z biomarker selection and MS based sample classification.

A panel data analysis of the military expenditure-external debt nexus : evidence from six middle eastern countries

While a number of studies examine the nexus between military expenditure and economic growth, little consideration has been give to the effect of military expenditure on external debt. This article examines the impact of military expenditure and income on external debt for a panel of six Middle Eastern countries - Oman, Syria, Yemen, Bahrain, Iran, and Jordan - over the period 1988 to 2002. The Middle East represents an interesting study of the effect of military expenditure on external debt because it has one of the highest rates of arms imports in the world and it is one of the most indebted regions in the world. The study first establishes whether there is a long-run relationship between military expenditure, income, and external debt in the six countries using a panel unit root and panel cointegration framework and then proceeds to estimate the long-run and short-run effects of military expenditure and income on external debt. The study finds that external debt is elastic with respect to military expenditure in the long run and inelastic with respect to military expenditure in the short run. For the panel of six Middle Eastern countries, in the long run a 1% increase in military expenditure results in between a 1.1 % and 1.6% increase in external debt, while a 1% increase in income reduces external debt by between 0.6% and 0.8%, depending on the specific estimator employed. In the short run, a 1% increase in military expenditure increases external debt by 0.2%, while the effect of income on external debt is statistically insignificant.

A panel data analysis of the determinants of oil consumption : the case of Australia

The goal of this paper is to examine the determinants of oil consumption for a panel consisting of six Australian States and one territory, namely Queensland, New South Wales, Victoria, Tasmania, South Australia, Western Australia, and the Northern territory, for the period 1985–2006. We find that oil consumption, oil prices and income are panel cointegrated. We estimate long-run elasticities and find that oil prices have had a statistically insignificant impact on oil consumption, while income has had a statistically significant positive effect on oil consumption.

Tourism and economic growth: a panel data analysis for Pacific Island countries

The contribution of tourism to the economic growth of Pacific Island countries (PICs) has achieved significance in the past decade. The shift in the economic policies of the PICs from the late 1980s has been decisively away from import substitution and agriculture to urban-based manufacturing and services sectors. Tourism is the main component of the services sector in the PICs. The contribution of tourism to economic growth in Fiji, Tonga, the Solomon Islands and Papua New Guinea is expected to grow. The authors use panel data for the four PICs to test the long-run relationship between real GDP and real tourism exports. They find support for panel cointegration and the results suggest that a 1% increase in tourism exports increases GDP by 0.72% in the long run and by 0.24% in the short run.

An agent-based hybrid system for microarray data analysis

This article reports our experience in agent-based hybrid construction for microarray data analysis. The contributions are twofold: We demonstrate that agent-based approaches are suitable for building hybrid systems in general, and that a genetic ensemble system is appropriate for microarray data analysis in particular. Created using an agent-based framework, this genetic ensemble system for microarray data analysis excels in both sample classification accuracy and gene selection reproducibility.

An embedded two-layer feature selection approach for microarray data analysis

Feature selection is an important technique in dealing with application problems with large number of variables and limited training samples, such as image processing, combinatorial chemistry, and microarray analysis. Commonly employed feature selection strategies can be divided into filter and wrapper. In this study, we propose an embedded two-layer feature selection approach to combining the advantages of filter and wrapper algorithms while avoiding their drawbacks. The hybrid algorithm, called GAEF (Genetic Algorithm with embedded filter), divides the feature selection process into two stages. In the first stage, Genetic Algorithm (GA) is employed to pre-select features while in the second stage a filter selector is used to further identify a small feature subset for accurate sample classification. Three benchmark microarray datasets are used to evaluate the proposed algorithm. The experimental results suggest that this embedded two-layer feature selection strategy is able to improve the stability of the selection results as well as the sample classification accuracy.

The productivity-wage and productivity-employment nexus : a panel data analysis of Indian manufacturing

This article investigates the long-run relationship between labour productivity and employment, and between labour productivity and real wages in the case of the Indian manufacturing sector. The panel data set consists of 17 two-digit manufacturing industries for the period 1973–1974 to 1999–2001. We find that productivity-wages and productivity-employment are panel cointegrated for all industries. We find that both employment and real wages exert a positive effect on labour productivity. We argue that flexible labour market has a significant influence on manufacturing productivity, employment and real wages in the case of Indian manufacturing.

Incorporating domain knowledge with video and voice data analysis in news broadcasts

This paper addresses the area of video annotation, indexing and retrieval, and shows how a set of tools can be employed, along with domain knowledge, to detect narrative structure in broadcast news. The initial structure is detected using low-level audio visual processing in conjunction with domain knowledge. Higher level processing may then utilize the initial structure detected to direct processing to improve and extend the initial classification.

The structure detected breaks a news broadcast into segments, each of which contains a single topic of discussion. Further the segments are labeled as a) anchor person or reporter, b) footage with a voice over or c) sound bite. This labeling may be used to provide a summary, for example by presenting a thumbnail for each reporter present in a section of the video. The inclusion of domain knowledge in computation allows more directed application of high level processing, giving much greater efficiency of effort expended. This allows valid deductions to be made about structure and semantics of the contents of a news video stream, as demonstrated by our experiments on CNN news broadcasts.

A generalised data analysis approach for baggage handling systems simulation

Airport baggage handling systems are a critical infrastructure component within major airports, and essential to ensure smooth luggage transfer while preventing dangerous material being loaded onto aircraft. This paper proposes a standard set of measures to assess the expected performance of a baggage handling system through discrete event simulation. These evaluation methods also have application in the study of general network systems. Results from the application of these methods reveal operational characteristics of the studied BHS, in terms of metrics such as peak throughput, in-system time and system recovery time.