Environmental Injustice in the United States: Myths and Realities

By James P. Lester; David W. Allen et al. | Go to book overview

tire set of intermediate reduced equations--and, for the sake of simplicity, discuss only the final reduced equations. 14

We have three final comments to make. First, we noted a problem with skewed distributions on both independent and dependent variables that had the potential to adversely affect all statistical tests. To eliminate this problem, we normalized our data to the extent possible. We did this through a combination of recoding extreme values and, in some instances, using either a log linear or square root transformation (in accordance with procedures recommended by Tabachnick and Fiddell, 1989:68-89).

Second, we were interested in determining if conditional effects were present. To assess interactive effects, we created exhaustive sets of terms from our pool of independent variables and entered these terms one at a time. The term was retained if it achieved significance at the p < .05 level. Since this aspect of the analysis was exploratory--since interactive terms are usually not considered unless there is some prior theoretical justifications for their existence--we treat these results as advisory and recommend other researchers try to replicate our findings.

In order to test for conditional effects, we adopted the technique recommended primarily by R. J. Friedrich ( 1982) but repeated and explained elsewhere ( Aiken and West, 1991; Cohen and Cohen, 1983:301-350). This technique requires that all variables are standardized before construction of interactive terms and that the equations be generated on the basis of standardized data. Under these conditions, reported results are regression coefficients (b) based on the standardized data.

Finally, multicollinearity is a problem with the type of data and measures we are using. We minimize this problem, in part, through the use of factor scales to subsume highly correlated measures of the same concept (for example, our social class scale). However, the problem could not be completely eliminated, and the data being the data, we simply had to accept that uncorrelated measures of the concepts of interest were simply not available. In order to produce a complete picture, we reproduce the tolerance statistics for each of our equations. Tolerance scores, which range from 0.00 to 1.00, indicate the degree of multicollinearity for respective independent variables and are interpreted as the smaller the tolerance score, the higher the level of multicollinearity. We note that the vast majority of the literature on the subject of environmental injustice does not report this statistic.


Summary

In this chapter, we have articulated the model that guides the analysis, its concepts and measures, the hypotheses that we will examine at the state, county, and city levels, and the method of analysis employed. In Chapters

-73-

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Environmental Injustice in the United States: Myths and Realities
Table of contents

Table of contents

  • Title Page iii
  • Dedications v
  • Contents vii
  • Figures and Tables ix
  • Preface and Acknowledgments xiii
  • 1 - Introduction the Nature of the Problem 1
  • Notes 7
  • 2 - Environmental Injustice Research: Reviewing the Evidence 9
  • Notes 18
  • 3 - Environmental Justice: Getting on the Public Agenda 21
  • Summary and Conclusions 51
  • Notes 52
  • 4 - Modeling Environmental Injustice: Concepts, Measures, Hypotheses, and Method of Analysis 57
  • Summary 73
  • Notes 74
  • 5 - Environmental Injustice in America's States 79
  • Notes 106
  • 6 - Environmental Injustice in America's Counties 113
  • Conclusion 129
  • Notes 131
  • 7 - Environmental Injustice in America's Cities 133
  • Conclusion 144
  • Notes 147
  • 8 - Summary and Conclusions from the Multilevel Analyses 149
  • Conclusion 156
  • Note 157
  • 9 - Existing Federal and State Policies for Environmental Justice: Problems and Prospects 159
  • Summary and Conclusion 171
  • Summary and Conclusion 171
  • 10 - Designing an Effective Policy for Environmental Justice: Implications and Recommendations 173
  • Conclusion 187
  • Notes 188
  • References 189
  • About the Authors 203
  • Index 205
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