Data splitting as a countermeasure against hypothesis fishing: with a case study of predictors for low back pain

There is growing concern in the scientific community that many published scientific findings may represent spurious patterns that are not reproducible in independent data sets. A reason for this is that significance levels or confidence intervals are often applied to secondary variables or sub-samples within the trial, in addition to the primary hypotheses (multiple hypotheses). This problem is likely to be extensive for population-based surveys, in which epidemiological hypotheses are derived after seeing the data set (hypothesis fishing). We recommend a data-splitting procedure to counteract this methodological problem, in which one part of the data set is used for identifying hypotheses, and the other is used for hypothesis testing. The procedure is similar to two-stage analysis of microarray data. We illustrate the process using a real data set related to predictors of low back pain at 14-year follow-up in a population initially free of low back pain. “Widespreadness” of pain (pain reported in several other places than the low back) was a statistically significant predictor, while smoking was not, despite its strong association with low back pain in the first half of the data set. We argue that the application of data splitting, in which an independent party handles the data set, will achieve for epidemiological surveys what pre-registration has done for clinical studies

Factors influencing epiphytic bryophyte and lichen species richness at different spatial scales in managed temperate forests

The effect of management related factors on species richness of epiphytic bryophytes and lichens was studied in managed deciduous-coniferous mixed forests in Western-Hungary. At the stand level, the potential explanatory variables were tree species composition, stand structure, microclimate and light conditions, landscape and historical variables; while at tree level host tree species, tree size and light were studied. Species richness of the two epiphyte groups was positively correlated. Both for lichen and bryophyte plot level richness, the composition and diversity of tree species and the abundance of shrub layer were the most influential positive factors. Besides, for bryophytes the presence of large trees, while for lichens amount and heterogeneity of light were important. Tree level richness was mainly determined by host tree species for both groups. For bryophytes oaks, while for lichens oaks and hornbeam turned out the most favourable hosts. Tree size generally increased tree level species richness, except on pine for bryophytes and on hornbeam for lichens. The key variables for epiphytic diversity of the region were directly influenced by recent forest management; historical and landscape variables were not influential. Forest management oriented to the conservation of epiphyte s should focus on: (i) the maintenance of tree species diversity in mixed stands; (ii) increment the proportion of deciduous trees (mainly oaks); (iii) conserving large trees within the stands; (iv) providing the presence of shrub and regeneration layer; (v) creating heterogeneous light conditions. For these purposes tree selection and selective cutting management seem more appropriate than shelterwood system

Further insights into the operation of the Chinese number system: Competing effects of Arabic and Mandarin number formats

Here we report the results of a speeded relative quantity task with Chinese participants. On each trial a single numeral (the probe) was presented and the instructions were to respond as to whether it signified a quantity less than or greater than five (the standard). In separate blocks of trials, the numerals were either presented in Mandarin or in Arabic number formats. In addition to the standard influence of numerical distance, a significant predictor of performance was the degree of physical similarity between the probe and the standard as depicted in Mandarin. Additionally, competing effects of physical similarity, defined in terms of the Arabic number format, were also found. Critically the size of these different effects of physical similarity varied systematically across individuals such that larger effects of one compensated for smaller effects of the other. It is argued that the data favor accounts of processing that assume that different number formats access different format-specific representations of quantities. Moreover, for Chinese participants the default is to translate numerals into a Mandarin format prior to accessing quantity information. The efficacy of this translation process is itself influenced by a competing tendency to carry out a translation into Arabic format

When One Size Does Not Fit All: A Simple Statistical Method to Deal with Across-Individual Variations of Effects

In science, it is a common experience to discover that although the investigated effect is very clear in some individuals, statistical tests are not significant because the effect is null or even opposite in other individuals. Indeed, t-tests, Anovas and linear regressions compare the average effect with respect to its inter-individual variability, so that they can fail to evidence a factor that has a high effect in many individuals (with respect to the intra-individual variability). In such paradoxical situations, statistical tools are at odds with the researcher’s aim to uncover any factor that affects individual behavior, and not only those with stereotypical effects. In order to go beyond the reductive and sometimes illusory description of the average behavior, we propose a simple statistical method: applying a Kolmogorov-Smirnov test to assess whether the distribution of p-values provided by individual tests is significantly biased towards zero. Using Monte-Carlo studies, we assess the power of this two-step procedure with respect to RM Anova and multilevel mixed-effect analyses, and probe its robustness when individual data violate the assumption of normality and homoscedasticity. We find that the method is powerful and robust even with small sample sizes for which multilevel methods reach their limits. In contrast to existing methods for combining p-values, the Kolmogorov-Smirnov test has unique resistance to outlier individuals: it cannot yield significance based on a high effect in one or two exceptional individuals, which allows drawing valid population inferences. The simplicity and ease of use of our method facilitates the identification of factors that would otherwise be overlooked because they affect individual behavior in significant but variable ways, and its power and reliability with small sample sizes (<30–50 individuals) suggest it as a tool of choice in exploratory studies

Evidence for alterations in fixational eye movements in glaucoma

BACKGROUND: Fixation changes in glaucoma are generally overlooked, as they are not strikingly evident as in macular diseases. Fundus perimetry might give additional insights into this aspect, along with traditional perimetric measures. In this work we propose a novel method to quantify glaucomatous changes in fixation features as detected by fundus perimetry and relate them to the extent of glaucomatous damage. METHODS: We retrospectively analysed fixation data from 320 people (200 normal subjects and 120 with glaucoma) from the Preferred Retinal Locus (PRL) detection of a Compass perimeter. Fixation stability was measured as Bivariate Contour Ellipse Area (BCEA), and using two novel metrics: (1) Mean Euclidean Distance (MED) from the Preferred Retinal Locus, and (2) Sequential Euclidean Distance (SED) of sequential fixation locations. These measures were designed to capture the spread of fixation points, and the frequency of position changes during fixation, respectively. RESULTS: In the age corrected analysis, SED was significantly greater in glaucomatous subjects than controls (P = 0.002), but there was no difference in BCEA (P = 0.15) or MED (P = 0.054). Similarly, SED showed a significant association with Mean Deviation (P  0.14 for both). CONCLUSION: Changes in the scanning pattern detected by SED are better than traditional measures of fixation spread (BCEA) for describing the changes in fixation stability observed in glaucoma

Mothers Matter Too: Benefits of Temperature Oviposition Preferences in Newts

The maternal manipulation hypothesis states that ectothermic females modify thermal conditions during embryonic development to benefit their offspring (anticipatory maternal effect). However, the recent theory suggests that the ultimate currency of an adaptive maternal effect is female fitness that can be maximized also by decreasing mean fitness of individual offspring. We evaluated benefits of temperature oviposition preferences in Alpine newts (Ichthyosaura [formerly Triturus] alpestris) by comparing the thermal sensitivity of maternal and offspring traits across a range of preferred oviposition temperatures (12, 17, and 22°C) and by manipulating the egg-predation risk during oviposition in a laboratory thermal gradient (12–22°C). All traits showed varying responses to oviposition temperatures. Embryonic developmental rates increased with oviposition temperature, whereas hatchling size and swimming capacity showed the opposite pattern. Maternal oviposition and egg-predation rates were highest at the intermediate temperature. In the thermal gradient, females oviposited at the same temperature despite the presence of caged egg-predators, water beetles (Agabus bipustulatus). We conclude that female newts prefer a particular temperature for egg-deposition to maximize their oviposition performance rather than offspring fitness. The evolution of advanced reproductive modes, such as prolonged egg-retention and viviparity, may require, among others, the transition from selfish temperature preferences for ovipositon to the anticipatory maternal effect

Testing for Differentially-Expressed MicroRNAs with Errors-in-Variables Nonparametric Regression

MicroRNA is a set of small RNA molecules mediating gene expression at post-transcriptional/translational levels. Most of well-established high throughput discovery platforms, such as microarray, real time quantitative PCR, and sequencing, have been adapted to study microRNA in various human diseases. The total number of microRNAs in humans is approximately 1,800, which challenges some analytical methodologies requiring a large number of entries. Unlike messenger RNA, the majority of microRNA (60%) maintains relatively low abundance in the cells. When analyzed using microarray, the signals of these low-expressed microRNAs are influenced by other non-specific signals including the background noise. It is crucial to distinguish the true microRNA signals from measurement errors in microRNA array data analysis. In this study, we propose a novel measurement error model-based normalization method and differentially-expressed microRNA detection method for microRNA profiling data acquired from locked nucleic acids (LNA) microRNA array. Compared with some existing methods, the proposed method significantly improves the detection among low-expressed microRNAs when assessed by quantitative real-time PCR assay

Modelling a response as a function of high frequency count data: the association between physical activity and fat mass

We present a new statistical modelling approach where the response is a function of high frequency count data. Our application is about investigating the relationship between the health outcome fat mass and physical activity (PA) measured by accelerometer. The accelerometer quantifies the intensity of physical activity as counts per epoch over a given period of time. We use data from the Avon longitudinal study of parents and children (ALSPAC) where accelerometer data is available as a time series of accelerometer counts per minute over seven days for a subset of children. In order to compare accelerometer profiles between individuals and to reduce the high dimension a functional summary of the profiles is used. We use the histogram as a functional summary due to its simplicity, suitability and ease of interpretation. Our model is an extension of generalised regression of scalars on functions or signal regression. It allows also multi-dimensional functional predictors and additive non-linear predictors for metric covariates. The additive multidimensional functional predictors allow investigating specific questions about whether the effect of PA varies over its intensity, by gender, by time of day or by day of the week. The key feature of the model is that it utilises the full profile of measured PA without requiring cut-points defining intensity levels for light, moderate and vigorous activity. We show that the (not necessarily causal) effect of PA is not linear and not constant over the activity intensity. Also, there is little evidence to suggest that the effect of PA intensity varies by gender or whether it happens on weekdays or on weekends

Physiogenomic analysis of weight loss induced by dietary carbohydrate restriction

BACKGROUND: Diets that restrict carbohydrate (CHO) have proven to be a successful dietary treatment of obesity for many people, but the degree of weight loss varies across individuals. The extent to which genetic factors associate with the magnitude of weight loss induced by CHO restriction is unknown. We examined associations among polymorphisms in candidate genes and weight loss in order to understand the physiological factors influencing body weight responses to CHO restriction. METHODS: We screened for genetic associations with weight loss in 86 healthy adults who were instructed to restrict CHO to a level that induced a small level of ketosis (CHO ~10% of total energy). A total of 27 single nucleotide polymorphisms (SNPs) were selected from 15 candidate genes involved in fat digestion/metabolism, intracellular glucose metabolism, lipoprotein remodeling, and appetite regulation. Multiple linear regression was used to rank the SNPs according to probability of association, and the most significant associations were analyzed in greater detail. RESULTS: Mean weight loss was 6.4 kg. SNPs in the gastric lipase (LIPF), hepatic glycogen synthase (GYS2), cholesteryl ester transfer protein (CETP) and galanin (GAL) genes were significantly associated with weight loss. CONCLUSION: A strong association between weight loss induced by dietary CHO restriction and variability in genes regulating fat digestion, hepatic glucose metabolism, intravascular lipoprotein remodeling, and appetite were detected. These discoveries could provide clues to important physiologic adaptations underlying the body mass response to CHO restriction

Out of Sight but Not Out of Mind? Behavioral Coordination in Red-Tailed Sportive Lemurs (Lepilemur ruficaudatus)

Many animals are organized into social groups and have to synchronize their activities to maintain group cohesion. Although activity budgets, habitat constraints, and group properties may impact on behavioural synchrony, little is known regarding how members of a group reach a consensus on the timing of activities such as foraging bouts. Game theory predicts that pair partners should synchronize their activities when there is an advantage of foraging together. As a result of this synchronization, differences in the energetic reserves of the two players develop spontaneously and the individual with lower reserves emerges as a pacemaker of the synchrony. Here, we studied the behavioral synchrony of pair-living, nocturnal, red-tailed sportive lemurs (Lepilemur ruficaudatus). We observed 8 pairs continuously for ≥1 annual reproductive cycle in Kirindy Forest, Western Madagascar. During focal observations, one observer followed the female of a pair and, simultaneously, another observer followed the male. We recorded the location and behavioral state of the focal individual every 5 min via instantaneous sampling. Although behavioral synchrony of pair partners appeared to be due mainly to endogenous activity patterns, they actively synchronized when they were in visual contact (<10 m). Nevertheless, red-tailed sportive lemurs benefit from synchronizing their activity only for 15% of the time, when they are close together. The lack of an early warning system for predators and weak support for benefits via social information transfer in combination with energetic constraints may explain why red-tailed sportive lemurs do not spend more time together and thus reap the benefits of behavioral synchrony