A Survey on Survey Statistics: What is done, can be done in Stata, and what's missing

Among survey statisticians Stata is increasingly recognized as one of the more powerful statistical software packages for the analysis of complex survey data. This paper will survey the capabilities of Stata to analyze complex survey data. We will briefly review and compare different methods for variance estimation for stratified and clustered samples, and discuss the handling of survey weights. Examples will be given for the practical importance of Stata's survey capabilities. In addition we will point to statistical solutions that aren't yet part of the official package, and review user written ados that currently extend Stata's survey capabilities. Among the specific topics we will cover are replication variance estimation (jackknife, balanced repeated replication, and the bootstrap), issues associated with degrees of freedom and domain estimates, quantile estimation, and some concerns related to model fitting using survey data.

Adjusted Logistic Propensity Weighting Methods for Population Inference using Nonprobability Volunteer-Based Epidemiologic Cohorts

Many epidemiologic studies forgo probability sampling and turn to nonprobability volunteer-based samples because of cost, response burden, and invasiveness of biological samples. However, finite population inference is difficult to make from the nonprobability samples due to the lack of population representativeness. Aiming for making inferences at the population level using nonprobability samples, various inverse propensity score weighting (IPSW) methods have been studied with the propensity defined by the participation rate of population units in the nonprobability sample. In this paper, we propose an adjusted logistic propensity weighting (ALP) method to estimate the participation rates for nonprobability sample units. Compared to existing IPSW methods, the proposed ALP method is easy to implement by ready-to-use software while producing approximately unbiased estimators for population quantities regardless of the nonprobability sample rate. The efficiency of the ALP estimator can be further improved by scaling the survey sample weights in propensity estimation. Taylor linearization variance estimators are proposed for ALP estimators of finite population means that account for all sources of variability. The proposed ALP methods are evaluated numerically via simulation studies and empirically using the na\"ive unweighted National Health and Nutrition Examination Survey III sample, while taking the 1997 National Health Interview Survey as the reference, to estimate the 15-year mortality rates

Calibrating non‐probability surveys to estimated control totals using LASSO, with an application to political polling

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148260/1/rssc12327.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148260/2/rssc12327_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148260/3/rssc12327-sup-0001-Appendix.pd

A unified in vitro evaluation for apatite-forming ability of bioactive glasses and their variants

The aim of this study was to propose and validate a new unified method for testing dissolution rates of bioactive glasses and their variants, and the formation of calcium phosphate layer formation on their surface, which is an indicator of bioactivity. At present, comparison in the literature is difficult as many groups use different testing protocols. An ISO standard covers the use of simulated body fluid on standard shape materials but it does not take into account that bioactive glasses can have very different specific surface areas, as for glass powders. Validation of the proposed modified test was through round robin testing and comparison to the ISO standard where appropriate. The proposed test uses fixed mass per solution volume ratio and agitated solution. The round robin study showed differences in hydroxyapatite nucleation on glasses of different composition and between glasses of the same composition but different particle size. The results were reproducible between research facilities. Researchers should use this method when testing new glasses, or their variants, to enable comparison between the literature in the future

Don't Let Me Be Misunderstood: Comparing Intentions and Perceptions in Online Discussions

Discourse involves two perspectives: a person's intention in making an utterance and others' perception of that utterance. The misalignment between these perspectives can lead to undesirable outcomes, such as misunderstandings, low productivity and even overt strife. In this work, we present a computational framework for exploring and comparing both perspectives in online public discussions. We combine logged data about public comments on Facebook with a survey of over 16,000 people about their intentions in writing these comments or about their perceptions of comments that others had written. Unlike previous studies of online discussions that have largely relied on third-party labels to quantify properties such as sentiment and subjectivity, our approach also directly captures what the speakers actually intended when writing their comments. In particular, our analysis focuses on judgments of whether a comment is stating a fact or an opinion, since these concepts were shown to be often confused. We show that intentions and perceptions diverge in consequential ways. People are more likely to perceive opinions than to intend them, and linguistic cues that signal how an utterance is intended can differ from those that signal how it will be perceived. Further, this misalignment between intentions and perceptions can be linked to the future health of a conversation: when a comment whose author intended to share a fact is misperceived as sharing an opinion, the subsequent conversation is more likely to derail into uncivil behavior than when the comment is perceived as intended. Altogether, these findings may inform the design of discussion platforms that better promote positive interactions.Comment: Proceedings of The Web Conference (WWW) 202