One Road to Riches?

Building effective state institutions before introducing democracy is widely presumed to improve different development outcomes. Conversely, proponents of this “stateness-first” argument anticipate that democratization before state building yields poor development outcomes. In this Element, we discuss several strong assumptions that (different versions of) this argument rests upon and critically evaluate the existing evidence base. In extension, we specify various observable implications. We then subject the stateness-first argument to multiple tests, focusing on economic growth as an outcome. First, we conduct historical case studies of two countries with different institutional sequencing histories, Denmark and Greece, and assess the stateness-first argument (e.g., by using a synthetic control approach). Thereafter, we draw on an extensive global sample of about 180 countries, measured across 1789–2019 and leverage panel regressions, preparametric matching, and sequence analysis to test a number of observable implications. Overall, we find little evidence to support the stateness-first argument.

Is Retrieval Practice Always Superior to Restudy?

A classic study by Roediger and Karpicke (2006a) investigated the relative benefits of restudy versus retrieval practice, or “test”, on memory retention. Repeated studying was superior to repeated testing when memory was tested immediately (all study > multiple study/single test > single study/multiple tests). Strikingly, the pattern reversed when memory was tested after a days-long delay, with best performance in a single study/multiple tests condition. As each study period was minutes-long and contained repeated reading of a to-be-remembered text passage, we were interested whether the striking benefit for repeated testing at the expense of any restudy replicates when study opportunities are brief, akin to a single mention of a fact in a lecture. Participants encountered academically relevant facts a total of three times, each time either studied (S) or self-tested (T). Final test followed immediately or after a delay (Experiment 1: two days, Experiment 2: seven days). Partially replicating prior work, immediate memory benefited from repeated study (SSS > SST > STT), but the pattern did not reverse after a delay. Instead, memory was superior for facts the were restudied in addition to self-tested (SST > STT = SSS). We further investigated whether restudy after a test (STS) provides additional benefits compared to restudy before test (SST), but found comparably high delayed recall in both conditions. The results show that under some circumstances, balancing repetition and testing can allow for more information to be learned and retained long-term.

maat: An R Package for Multiple Administrations Adaptive Testing

Multiple Administrations Adaptive Testing (MAAT) is an extension of the shadow-test approach to CAT for the assessment framework involving multiple tests administered periodically throughout the year. The maat package utilizes multiple item pools vertically scaled across grades and multiple phases (stages) within each test administration, allowing for transitioning from an item pool to another as deemed necessary to further enhance the quality of assessment.

A novel algorithm to flag columns associated in any way with others or a dependent variable is computationally tractable in large data matrices and has much higher power when columns are linked like mutations in chromosomes

ABSTRACTWhen a data matrix DM has many independent variables IVs, it is not computationally tractable to assess the association of every distinct IV subset with the dependent variable DV of the DM, because the number of subsets explodes combinatorially as IVs increase. But model selection and correcting for multiple tests is complex even with few IVs.DMs in genomics will soon summarize millions of markers (mutations) and genomes. Searching exhaustively in such DMs for mutations that alone or synergistically with others are associated with a trait is computationally tractable only for 1- and 2-mutation effects. This is also why population geneticists study mainly 2-marker combinations.I present a computationally tractable, fully parallelizable Participation in Association Score (PAS) that in a DM with markers detects one by one every column that is strongly associated in any way with others. PAS does not examine column subsets and its computational cost grows linearly with the number of columns, remaining reasonable even when DMs have millions of columns. PAS P values are readily obtained by permutation and accurately Sidak-corrected for multiple tests, bypassing model selection. The P values of a column’s PASs and dvPASs for different orders of association are i.i.d. and easily turned into a single P value.PAS exploits how associations of markers in the rows of a DM cause associations of matches in the pairwise comparisons of the rows. For every such comparison with a match at a tested column, PAS computes the matches at other columns by modifying the comparison’s total matches (scored once per DM), yielding a distribution of conditional matches that reacts diagnostically to the associations of the tested column. Equally computationally tractable is dvPAS that flags DV-associated IVs by also probing the matches at the DV.Simulations show that i) PAS and dvPAS generate uniform-(0,1)-distributed type I error in null DMs and ii) detect randomly encountered binary and trinary models of significant n-column association and n-IV association to a binary DV, respectively, with power in the order of magnitude of exhaustive evaluation’s and false positives that are uniform-(0,1)-distributed or straightforwardly tuned to be so. Power to detect 2-way associations that extend over 100+ columns is non-parametrically ultimate but that to detect pure n-column associations and pure n-IV DV associations sinks exponentially with increasing n.Important for geneticists, dvPAS power increases about twofold in trinary vs. binary DMs and by orders of magnitude with markers linked like mutations in chromosomes, specially in trinary DMs where furthermore dvPAS fine-maps with highest resolution.

Formalizing Statistical Beliefs in Hypothesis Testing Using Program Logic

We propose a new approach to formally describing the requirement for statistical inference and checking whether the statistical method is appropriately used in a program. Specifically, we define belief Hoare logic (BHL) for formalizing and reasoning about the statistical beliefs acquired via hypothesis testing. This logic is equipped with axiom schemas for hypothesis tests and rules for multiple tests that can be instantiated to a variety of concrete tests. To the best of our knowledge, this is the first attempt to introduce a program logic with epistemic modal operators that can specify the preconditions for hypothesis tests to be applied appropriately.

Biomarkers of mammographic density in premenopausal women

Background While mammographic density is one of the strongest risk factors for breast cancer, little is known about its determinants, especially in young women. We applied targeted metabolomics to identify circulating metabolites specifically associated with mammographic density in premenopausal women. Then, we aimed to identify potential correlates of these biomarkers to guide future research on potential modifiable determinants of mammographic density. Methods A total of 132 metabolites (acylcarnitines, amino acids, biogenic amines, glycerophospholipids, sphingolipids, hexose) were measured by tandem liquid chromatography/mass spectrometry in plasma samples from 573 premenopausal participants in the Mexican Teachers’ Cohort. Associations between metabolites and percent mammographic density were assessed using linear regression models, adjusting for breast cancer risk factors and accounting for multiple tests. Mean concentrations of metabolites associated with percent mammographic density were estimated across levels of several lifestyle and metabolic factors. Results Sphingomyelin (SM) C16:1 and phosphatidylcholine (PC) ae C30:2 were inversely associated with percent mammographic density after correction for multiple tests. Linear trends with percent mammographic density were observed for SM C16:1 only in women with body mass index (BMI) below the median (27.4) and for PC ae C30:2 in women with a BMI over the median. SM C16:1 and PC ae C30:2 concentrations were positively associated with cholesterol (total and HDL) and inversely associated with number of metabolic syndrome components. Conclusions We identified new biomarkers associated with mammographic density in young women. The association of these biomarkers with mammographic density and metabolic parameters may provide new perspectives to support future preventive actions for breast cancer.

Are Multiple Tests Necessary for Salivary Pepsin Detection in the Diagnosis of Laryngopharyngeal Reflux?

Objectives To evaluate the necessity of multiple salivary pepsin tests within a day when diagnosing laryngopharyngeal reflux. Study Design Prospective cohort study. Setting Tertiary hospitals. Methods A total of 138 patients with signs and/or symptoms associated with laryngopharyngeal reflux were included. Salivary pepsin was detected on the day of 24-hour pH monitoring, and the results of salivary pepsin detected once in the morning and multiple times in 1 day were compared with the results of pH monitoring. Results Among the 138 patients, pH monitoring results were positive in 112. Salivary pepsin was positive in 47 cases in the morning, which was not consistent with the results of pH monitoring (kappa value = 0.117). With the pH monitoring results as the standard, the salivary pepsin detected once in the morning had a sensitivity of 38.4% (43/112) and a specificity of 84.6% (22/26) for the diagnosis of laryngopharyngeal reflux. When salivary pepsin was detected multiple times per day, 102 patients tested positive. The consistency with pH monitoring was moderate (kappa value = 0.587). The sensitivity was 86.6% (97/112), and the specificity was 80.8% (21/26). Of the 97 patients with positive results from pH monitoring and salivary pepsin detected multiple times a day, 54 had negative findings for a single detection in the morning, indicating that 55.7% (54/97) of the true positive cases were missed. Conclusion Although a single detection of salivary pepsin in the morning is more economical, the sensitivity is too low, and it is necessary to detect it multiple times a day.

Experts’ opinion on the detection and management of prediabetes in Lebanon

Given that the complications of type 2 diabetes can start at an early stage, early detection and appropriate management of prediabetes are essential. We aimed to develop an expert opinion on prediabetes in Lebanon to pave the way for national guidelines tailored for the Lebanese population in the near future. A panel of seven diabetes experts conducted a thorough literature review and discussed their opinions and experiences before coming up with a set of preliminary recommendations for the detection and management of prediabetes in Lebanon. Lebanese physicians employ multiple tests for the diagnosis of prediabetes and no national cut-off values exist. The panel agreed that prediabetes screening should be focused on patients exceeding 45 years of age with otherwise no risk factors and on adults with risk factors. The panel reached that fasting plasma glucose (FPG) and HbA1c should be used for prediabetes diagnosis in Lebanon. FPG values of 100–125 mg/dL or HbA1c values of 5.7%–6.4% were agreed upon as indicative of prediabetes. For the management of prediabetes, a three-step approach constituting lifestyle modifications, pharmacological treatment and bariatric surgery is recommended. There should be more focus on research on prediabetes in Lebanon. This preliminary report will be further discussed with the Lebanese Society of Endocrinology, Diabetes and Lipids in 2021 in order to come up with the first Lebanese national guidelines for the detection and management of prediabetes in Lebanon.

In search of a Goldilocks zone for credible AI

If artificial intelligence (AI) is to help solve individual, societal and global problems, humans should neither underestimate nor overestimate its trustworthiness. Situated in-between these two extremes is an ideal ‘Goldilocks’ zone of credibility. But what will keep trust in this zone? We hypothesise that this role ultimately falls to the social cognition mechanisms which adaptively regulate conformity between humans. This novel hypothesis predicts that human-like functional biases in conformity should occur during interactions with AI. We examined multiple tests of this prediction using a collaborative remembering paradigm, where participants viewed household scenes for 30 s vs. 2 min, then saw 2-alternative forced-choice decisions about scene content originating either from AI- or human-sources. We manipulated the credibility of different sources (Experiment 1) and, from a single source, the estimated-likelihood (Experiment 2) and objective accuracy (Experiment 3) of specific decisions. As predicted, each manipulation produced functional biases for AI-sources mirroring those found for human-sources. Participants conformed more to higher credibility sources, and higher-likelihood or more objectively accurate decisions, becoming increasingly sensitive to source accuracy when their own capability was reduced. These findings support the hypothesised role of social cognition in regulating AI’s influence, raising important implications and new directions for research on human–AI interaction.