Problems in the Analysis of Survey Data, and a Proposal

Morgan, James N.; Sonquist, John A.

doi:10.1080/01621459.1963.10500855

Cited by 875 publications

(192 citation statements)

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“…To better understand how multiple variables for media consumption and other demographics/activities related to SRD, a multivariate segmentation scheme was employed based on recursive partitioning (Morgan and Sonquist, 1963; Friedman, 1977; Breiman et al, 1984; Gordon and Olshen, 1984; Quinlan, 1986; Mingers, 1989). The first CHAID tree (Kass, 1980; Biggs et al, 1991) (Figure 4) shows the interaction among the predictor variables on the rate of SRD (the target variable).…”

Section: Resultsmentioning

confidence: 99%

“…First, we performed a descriptive statistical analysis, inclusive of correlations between depression and media consumption variables to facilitate interpretation of the subsequent analyses. Second, we used the results to inform a type of recursive partitioning (Morgan and Sonquist, 1963; Friedman, 1977; Breiman et al, 1984; Gordon and Olshen, 1984; Quinlan, 1986; Mingers, 1989), namely CHAID tree analysis (Kass, 1980; Biggs et al, 1991). Third, we performed a multivariate discriminate analysis.…”

Section: Methodsmentioning

confidence: 99%

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The relationship between self-report of depression and media usage

Block

Stern

Raman

et al. 2014

Front. Hum. Neurosci.

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Depression is a debilitating condition that adversely affects many aspects of a person's life and general health. Earlier work has supported the idea that there may be a relationship between the use of certain media and depression. In this study, we tested if self-report of depression (SRD), which is not a clinically based diagnosis, was associated with increased internet, television, and social media usage by using data collected in the Media Behavior and Influence Study (MBIS) database (N = 19,776 subjects). We further assessed the relationship of demographic variables to this association. These analyses found that SRD rates were in the range of published rates of clinically diagnosed major depression. It found that those who tended to use more media also tended to be more depressed, and that segmentation of SRD subjects was weighted toward internet and television usage, which was not the case with non-SRD subjects, who were segmented along social media use. This study found that those who have suffered either economic or physical life setbacks are orders of magnitude more likely to be depressed, even without disproportionately high levels of media use. However, among those that have suffered major life setbacks, high media users—particularly television watchers—were even more likely to report experiencing depression, which suggests that these effects were not just due to individuals having more time for media consumption. These findings provide an example of how Big Data can be used for medical and mental health research, helping to elucidate issues not traditionally tested in the fields of psychiatry or experimental psychology.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

The relationship between self-report of depression and media usage

Block

Stern

Raman

et al. 2014

Front. Hum. Neurosci.

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“…What is your opinion of the goals set by the parliament for large carnivores in Sweden? " A high degree of correlation (r p ) among the attitude items within each group of items (0.74 between the existence items and 0.71 between the policy items) encouraged the use of principal component analysis to avoid multicollinearity (Morgan and Sonquist 1963).…”

Section: Measurementsmentioning

confidence: 99%

Direct experience and attitude change towards bears and wolves

Eriksson¹,

Sandström²,

Ericsson

2015

Wildlife Biology

126

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Understanding how changes in the sizes of large carnivore populations aff ect the attitudes of the public is vital in order to mitigate social confl icts over large carnivore management issues. Using data from two Swedish postal surveys in 2004 and 2009, we examined the probable social eff ects of a continued increase in the Swedish populations of bear and wolf by comparing levels of direct experience of bears and wolves with public attitudes towards these animals. We report an increase in direct experience of bears and wolves, lower levels of acceptance of the existence of these animals, and a lower degree of support for the policy goals of both species in 2009 compared to 2004. We also fi nd that these changes are more prominent in areas with local carnivore populations than in other areas of Sweden. Our results imply that attitudes towards bears and wolves are likely to become more negative as populations continue to grow. Th e uneven distributions of the carnivore populations are likely to generate more frequent social confl icts in the future as they could cause an increase in the attitudinal divide between those members of the Swedish public who have had direct experiences of carnivores and those who have not.

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“…The first to appear was the Automatic Interaction Detection (AID), in which the outcome variable is quantitative (Morgan, Sonquist 1963). Several other algorithms followed such as Exploration of Links and Interaction through Segmentation of an Experimental Ensemble (ELISEE) (Cellard et al 1967) and THeta AID (THAID) (Morgan, Messenger 1973) for categorical response variable, and MAID (Gillo 1972) for quantitative response variable.…”

Section: Literature Reviewmentioning

confidence: 98%

A Data Mining Approach to Forecast Late Arrivals in a Transhipment Container Terminal

et al. 2014

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One of the most important issues in Transhipment Container Terminal (TCT) management is to have fairly reliable and affordable predictions about vessel arrival. Terminal operators need to estimate the actual time of arrival in port in order to determine the daily demand for each work shift with greater accuracy. In this way, the resources required (human resources, equipment as well as spatial resources) can be allocated more efficiently. Despite contractual obligations to notify the Estimated Time of Arrival (ETA) 24 hours before arrival, ship operators often have to revise it due to unexpected events like weather conditions, delay in a previous port and so on. For planners the decision-making processes related to this topic can sometimes be so complex without the support of suitable methodological tools. Specific models should be adopted, in a daily planning scenario, to provide a useful support tool in TCTs. In this study, we discuss an exploratory analysis of the data affecting delays registered at a Mediterranean TCT. We present some preliminary results obtained using data mining techniques and propose a Classification and Regression Trees (CART) model to reduce the range of uncertainty of ship arrivals in port. This approach is compulsory to manage vast amounts of unstructured data involved in estimating of vessel arrivals. Reference to this paper should be made as follows: Pani, C.; Fadda, P.; Fancello, G.; Frigau, L.; Mola, F. 2014. A data mining approach to forecast late arrivals in a transhipment container terminal, Transport 29(2): 175-184. http://dx.

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Problems in the Analysis of Survey Data, and a Proposal

Cited by 875 publications

References 0 publications

The relationship between self-report of depression and media usage

The relationship between self-report of depression and media usage

Direct experience and attitude change towards bears and wolves

A Data Mining Approach to Forecast Late Arrivals in a Transhipment Container Terminal

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