Sentence examples for control observations from inspiring English sources
In our MDiD method, we first perform propensity score matching with the aim of balancing the distribution of observable characteristics between treated and control observations.
Related to this is the balance of observable characteristics between treated and matched control observations.
The idea behind the PSM approach is to find control observations (that is, non-invaded households) having initial observable characteristics similar to the invaded households, to serve as valid surrogates for the missing counterfactuals.
Two additional columns in Table 5 in the Appendix show the number of treated and control observations before matching as well as the number of treated and control observations that are left after matching.
This method addresses the imbalance of baseline characteristics between the treated and control groups by reweighting control observations based on their propensity score; control observations with a higher propensity score are given a higher weight.
One of the important assumptions in propensity score matching is the overlap in the distribution of the estimated propensity scores for the treated and the control observations.
All pairs quickly habituated to the presence of earphones and speakers, and provisioning rates during control observation periods (see below) were typical of those observed at un-manipulated nests [37].
French philosopher Michel Foucault argued that a panopticon ably maintains social and power imbalances while using that most passive method of control: observation.
Female headed households are very different from their male counterparts, and 300 of them were in a stratum without any control observation.
Typical uses encompass, for example, observation of Earth; meteorology; monitoring of natural resources, agriculture, and forestry; pollution control; observation and prediction of natural disasters; and monitoring of critical infrastructure.
When an out-of- control observation has been detected, the probability of a level shift becomes: p ( B | A ′ ) = ( 1 - β ) p ( B ) ( 1 - β ) p ( B ) + α ( 1 - p ( B ) ) (3).
