51 household income is negatively related to the Project Participation Level Index. It should be noted that the
correlations of Kinabohutan with the indices are almost the mirror image of the correlations with Christian e.g., one is negative where the other is positive at similar levels. This is due to the differences in religious
preference between Kinabohutan and the rest of Talise; hence, it will be impossible to separate the effects of these two variables.
Once again, stepwise multiple regression is used to determine the
combinations of independent variables that impact project participation and knowledge
in Talise. Results of these analyses are in table 35. Education is once again the
principal predictor of the project participation and knowledge indices. There
is no multiple regression presented for the MPA Knowledge Index due to the fact that
once education was entered into the regression equation, the partial correlations
for religious preference and Kinabohutan reduced to 0.16 p0.05; hence, they were
not entered into the equation in the stepwise process. Once again the analyses indicate
that males and those with higher education tend to participate in and know about the
project. The relative importance of fishing to household income also influences
knowledge about the project. Overall the multiple regressions are modest, but
statistically significant.
4.2 Changes in Material Style Of Life
The question for monitoring concerns whether or not project activities have improved the coastal environment both natural and human
3
to the extent that existing productive activities have increased their livelihood both monetary and non-monetary income. In the absence of reliable income data, material style of
life is used as an indicator of level of livelihood; thus, changes in this indicator are assumed to reflect parallel changes in livelihood. This section of the report analyses the impacts Proyek Pesisir on material style of life.
4.2.1 Material Style of Life Scale
As a means of developing a standardized material style of life scale for all project and control sites, a principal component analysis was conducted for the 28 material style of life variables
4
for all ten project and control villages across the three time periods N = 1099 households. Five of the items manifested very low
component loadings in the first analysis of the data, so they were eliminated, and the analysis, using varimax rotation of components, was conducted once again. The scree test Cattell 1966 was used to determine the
number of components, resulting in 4 components which account for a total of 49 percent of the variance in the data set. The results of this analysis are found in Table 36. Items loading highest on the first component
indicate a relatively well-constructed house with adequate furnishings. Items loading highest on component two reflect modern appliances, and those with high positive loadings on factor three are associated with a solid,
permanent structure e.g., cement wall and floor and tin roof while those loading a high negative are associated
3
The natural environment includes the non-human aspects of the sea and its adjacent land-mass. The human environment includes the human populations, their multiple behaviors and the material aspects of these
behaviors e.g., their occupations, tools, housing, social behavior, etc..
4
See Pollnac and Crawford 2000 for a discussion of the use of principal component analysis with this type of data.
Table 35. Stepwise regression analyses of project participation and knowledge indices in Talise N=80.
DEPENDENT VARIABLE: PARTICIPATION INDEX STANDARDIZED
INDEPENDENT VARIABLE BETA COEFF. PROB. Education
0.381 0.001 Gender male 0.277 0.007
R=0.49 R
2
=0.24 Adj. R
2
=0.22 F=12.050 p 0.001 DEPENDENT VARIABLE: PARTICIPATION LEVEL
STANDARDIZED INDEPENDENT VARIABLE BETA COEFF. PROB.
Education 0.341 0.001
Kinabohutan -0.305 0.004 R=0.52 R
2
=0.27 Adj. R
2
=0.25 F=14.025 p 0.001 DEPENDENT VARIABLE: PROJECT KNOWLEDGE
STANDARDIZED INDEPENDENT VARIABLE BETA COEFF. PROB.
Education 0.450 0.001
Gender male 0.280 0.005
Importance of fishing 0.228 0.022 R=0.56 R
2
=0.31 Adj. R
2
=0.28 F=11.270 p 0.001
52 with a less permanent structure wood walls, floor, and window. Finally, those loading highest on component
four cupboard, chairs and modern stove are furnishings usually associated with a modern house. Component scores
representing the position of each household on each
component were created for each household. The
component scores are the sum of the component coefficients
times the sample standardized variables. These coefficients
are proportional to the component loadings. Hence,
items with high positive loadings contribute more
strongly to a positive component score than those
with low or negative loadings. Nevertheless, all items
contribute or subtract from the score; hence, items with
moderately high loadings on more than one component
e.g., tin roof and concrete wall in the analysis presented
here will contribute at a moderate level, although
differently, to the component scores associated with each of the components. This type of component score provides the best representation of the data. In this paper, for this data we will refer to these scores as Material
Style of Life MSL Component Scores. They are standardized scores with a mean of zero and a standard deviation of one.
4.2.2 Cross Community Analyses of Changes in Material Style of Life
