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Linear Regression
Published in Peter Cummings, Analysis of Incidence Rates, 2019
We know that homicide rates vary by sex, age, and other factors. We can think of 3.38 as the difference in the homicide rates for a person randomly sampled from the South compared with the rate for a randomly sampled person from New England. The sampling probability for an individual is equal to the inverse of the regional person-time; a Massachusetts resident has the same chance of being sampled as a Vermont resident. We interpret 3.38 as the difference in rates for the entire population of each region.
Basic Concepts and Analysis
Published in Ørnulf Borgan, Norman E. Breslow, Nilanjan Chatterjee, Mitchell H. Gail, Alastair Scott, Christopher J. Wild, Handbook of Statistical Methods for Case-Control Studies, 2018
For this sample, the sampling probability ratio is . When the logistic model without interaction is fit to these data, we obtain
S
Published in Filomena Pereira-Maxwell, Medical Statistics, 2018
A method for selecting a representative sample from a given population, in which the probability of being selected is the same for each individual. The method is carried out in a random fashion, so that the probability of an individual being selected from the population is also independent of his or her own characteristics. A sampling frame that enumerates each member of the population is necessary to carry out this sampling modality. Where the population cannot be enumerated, cluster and multistage sampling may provide an alternative way of carrying out random sampling. In addition to sample selection for surveys and cross-sectional studies, simple random sampling may also be employed to select the controls in a case-control study if the source population can be enumerated. Here, also, controls should be selected independently of their exposure status. See also sampling, probability sampling.
Psychological factors associated with protected sex among indirect female sex workers in Denpasar, Bali, Indonesia
Published in AIDS Care, 2020
I Gusti Ngurah Edi Putra, Dusita Phuengsamran, Aree Jampaklay, Panithee Thammawijaya, Pande Putu Januraga
Since this study employed cluster random sampling, the weighting issue was taken into account to produce correct calculation of population estimation based on samples collected. There were two steps used to calculate weight, consisting of base or design weight and post-stratification adjustment to known population total. For the first step, base weight was calculated as the reciprocal of sampling probability. With one-stage cluster random sampling, sampling probability was determined based on cluster selection only. Meanwhile, for the second step, the base weight was multiplied by the ratio between population of indirect FSWs and selected sample from each cluster. The same final weight was applied to each indirect FSW within the same cluster.
Diverse classifier ensemble creation based on heuristic dataset modification
Published in Journal of Applied Statistics, 2018
Hamid Jamalinia, Saber Khalouei, Vahideh Rezaie, Samad Nejatian, Karamolah Bagheri-Fard, Hamid Parvin
Another Bagging scheme is Roughly-Bagging that it is based on under-sampling. In spite of SMOTE-Bagging, it tries to equalize the sampling probability of each class. It does not try to fix sample size like SMOTE-Bagging. Indeed, while the size of minority class is fix, but the size of majority class is statistically determined. So the class distribution can be even somewhat imbalanced. But this slightly imbalanceness is in favor of the ensemble diversity. The both with-replacement and without-replacement strategies can be used in SMOTE-Bagging [5].
Effectiveness of cognitive behavioural therapy in reinforcing positive adaption among patients with substance use disorders in the Gaza Strip
Published in Journal of Substance Use, 2021
Osama Jabr Emad, Inshirah Mustafa Osman, Yousef Ibrahim Aljeesh
The sample consisted of 30 Patients with SUDs who were admitted to the Al-Amal Center in a psychiatric hospital in the Gaza Strip. The sample assigned randomly into two groups: experimental and control (15 per group). Each participant must be diagnosed with SUDs according to DSM-5 criteria by a psychiatrist with no comorbid with physical or psychiatric disorders. The type of sample is a simple random sampling (probability sample).