Type: test statistic
Measurement level: Correlate: metric, Happiness: metric
Theoretical range: unlimited

Meaning:  
b > 0   A higher correlate level corresponds with a higher happiness rating on average.
B < 0   A higher correlate level corresponds with a lower happiness rating on average.
B = 0   Not any correlation with the relevant correlate.

Only the sign of the computed coefficient is informative.

Happiness is an ordered categorical variable. Higher categories correspond to being more happy.

OPRC < 0 indicates that the probability of being beyond a chosen happiness category decreases and the probability of being at or below that category increases when

1) the corresponding metric correlate increases
2) the corresponding category of a categorical correlate is compared to the reference category.

OLRC > 0 indicates that the probability of being beyond a chosen happiness category
increases and the probablity of being at or below that category decreases when

1) the corresponding metric correlate increases
2) the corresponding category of a categorical correlate is compared to the reference category.

Type: test statistic
WDH symbol: b-fix
Primary correlate level: metric
Secondary correlate level: nonmetric
Happiness level: metric
Theoretical range: unlimited
Meaning:
Variant of  usual (non-standardized) regression coefficient (b), which controls for the secondary variables, by focusing on differences from a fixed level, such as the mean in a category. Aims to reduce  the residual variance and to improve the precision of the regression coefficient.

References:
Wikipedia: http://en.wikipedia.org/wiki/Fixed_effects_model
Non-technical text: http://www.jblumenstock.com/files/courses/econ174/FEModels.pdf

Type: test statistic
WDH symbol: b-fix
Primary correlate level: metric
Secondary correlate level: nonmetric
Happiness level: metric
Theoretical range: unlimited
Meaning:
Variant of  usual (non-standardized) regression coefficient (b), which controls for the secondary variables, by focusing on differences from a fixed level, such as the mean in a category. Aims to reduce  the residual variance and to improve the precision of the regression coefficient.

References:
Wikipedia: http://en.wikipedia.org/wiki/Fixed_effects_model
Non-technical text: http://www.jblumenstock.com/files/courses/econ174/FEModels.pdf