Censoring, Left and Right

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A comparison of nonparametric estimators of survival under left-truncation and right-censoring motivated by a case study

A comparison of nonparametric estimators of survival under left-truncation and right-censoring motivated by a case study

Figure 2 shows means, 5-th and 95-th percentile of their three resulting ap- proximate sampling distributions. Something unexpected can be seen: the NPMLE and the BFHE are almost exactly unbiased, whereas the INE is severely biased downward for most of the relevant range. The above-mentioned underes- timation problem slightly affects the 5th percentile of the NPMLE, but otherwise underestimation is not visible in its mean. This confirms that the two realizations of the NPMLE, the BFHE and the INE associated to the partial database are not exceptional: at least for this simulating scenario, which approximates the un- known scenario of the case study, the sampling distribution of the NPMLE and of the BFHE are better than the INE. This can be seen as a counterexample to different conclusions reached in Pan and Chappell (1998), where the INE is in- troduced mainly to correct the NPMLE. A strength of our findings is that simula- tions here approximate a real-life situation where severe truncation and censoring affect the data.
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Bootstrap intervals in the presence of left-truncation, censoring and covariates with a parametric distribution

Bootstrap intervals in the presence of left-truncation, censoring and covariates with a parametric distribution

ABSTRACT Left-truncated and censored survival data are commonly encountered in medical studies. However, traditional inferential methods that heavily rely on normality assumptions often fail when lifetimes of observations in a study are both truncated and censored. Thus, it is important to develop alternative inferential procedures that ease the assumptions of normality and unconventionally relies on the distribution of data in hand. In this research, a three parameter log-normal parametric survival model was extended to incorporate left-truncated and right censored medical data with covariates. Following that, bootstrap inferential procedures using non-parametric and parametric bootstrap samples were applied to the parameters of this model. The performance of the parameter estimates was assessed at various combinations of truncation and censoring levels via a simulation study. The recommended bootstrap intervals were applied to a lung cancer survival data.
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2 Right Censoring and Kaplan-Meier Estimator

2 Right Censoring and Kaplan-Meier Estimator

Left truncation occurs when the time to event of interest in the study sample is greater than a (left) truncation variable. For example, in a study of life expectancy (survival time measured from birth to death) using elderly residents in a retirement community (example 1.16, page 15 of Klein & Moeschberger), the individuals must survive to a sufficient age to enter the retirement community. Therefore, their survival time is left truncated by their age entering the community. Ignoring the truncation will lead to a biased sample and the survival time from the sample will over estimate the underlying life expectancy.
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Dynamic inference for non-Markov transition probabilities under random right-censoring

Dynamic inference for non-Markov transition probabilities under random right-censoring

Transition probabilities are essential quantities in survival analytic examinations of multi-state models. Under independent right-censoring, for instance, the Aalen–Johansen estimator assesses these probabilities optimally in nonparametric Markovian multi-state models; cf. Aalen (1978) and Section IV.4 in Andersen et al. (1993) for more details. The Markov assumption is crucial for the validity of the Aalen–Johansen estimator. However, in real world applications, it may be unrealistic to postulate such a structure: given the present patient’s state, future developments are often not independent of a severe past illness history. There have been several attempts
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A Simple Method to Estimate the Time-dependent ROC Curve Under Right Censoring

A Simple Method to Estimate the Time-dependent ROC Curve Under Right Censoring

The time-dependent Receiver Operating Characteristic (ROC) curve is often used to study the diagnostic accuracy of a single continuous biomarker, measured at baseline, on the onset of a disease condition when the disease onset may occur at different times during the follow-up and hence may be right censored. Due to censoring, the true disease onset status prior to the pre-specified time horizon may be unknown on some patients, which causes difficulty in calculating the time-dependent sensi- tivity and specificity. We study a simple method that adjusts for censoring by weighting the censored data by the conditional probability of disease onset prior to the time horizon given the biomarker and the observed censoring time. Our numerical study shows that the proposed method produces unbiased and efficient estimators of time-dependent sensitivity and specificity as well as area under the ROC curve, and outperforms several other published methods currently implemented in R packages.
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Nonparametric predictive inference with combined data under different right-censoring schemes.

Nonparametric predictive inference with combined data under different right-censoring schemes.

statistics framework that all samples are drawn from the same population. For exam- ple, one may wish to based inference on the combined information from two or more Type-II (or Type-I) right-censored samples, with different censoring times applying per sample. The combined data in this case can be represented as a single Type-II (or Type- I) progressively censored sample, for which NPI has been introduced by Maturi et al. (2010a). Moreover, if we combine two or more Type-II (or Type-I) progressively cen- sored samples we obtain a single Type-II (or Type-I) progressively censored sample. This means that we can apply the same inferential method as presented by Maturi et al. (2010a) on the resulting combined progressively censored sample, as discuss in detail in the rest of this section. This approach for combining information from samples un- der different censoring schemes is based on the approach presented by Balakrishnan et al. (2010). However, they study the problem from the order statistics perspective while we apply the NPI method to such scenarios to derive frequentist predictive in- ference for the next observation. Working with order statistics is complicated as it requires the distributions for the different order statistics. The proposed NPI approach is pretty flexible and implementation of the NPI lower and upper survival functions as presented in Section 2 is quite straightforward. With the usual, rather weak, assump- tions underlying NPI together with assumed non-informative right-censoring (assumed as rc-A (n) for each sample and for the combined sample) as discussed in Section 1, any
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Re-measuring left-right : a better model for extracting left-right political party policy preference scores

Re-measuring left-right : a better model for extracting left-right political party policy preference scores

Although there exists a reasonably strong correlation between the survey-based and the manifesto-based data (Gabel and Huber 2000),neither of these sources includes a measure of uncertainty with their estimates of party position. Within the manifesto-based research there has been a rich discussion as to how best use the data to construct a left-right dimension, but no discussion of assessing the uncertainty inherent in the process of estimating party positions. This limits the ability to discern whether or not di ff erent placements are statistically significantly di ff erent from one another. Given the importance of manifesto-based placements this could be an extremely important omission. That is, if one could estimate the uncertainty of these party placements, the significance of changes within party over time and di ff erences between parties in a party system could be accurately assessed.
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DETECTION OF LEFT-TO-RIGHT INTRACARDIAC SHUNTS

DETECTION OF LEFT-TO-RIGHT INTRACARDIAC SHUNTS

12. Inferior vena cava, low (at L4–L5) 13. Left ventricle 14. Aorta (distal to insertion of ductus) In performing the oximetry run, an end-hole catheter (e.g., Swan-Ganz balloon-flotation catheter) or one with side holes close to its tip (e.g., a Goodale-Lubin catheter) is positioned in the right or left pulmonary artery. Cardiac output is measured by the Fick method. As soon as the determination of oxygen consumption is completed, the operator begins to obtain 2-mL blood samples from each of the locations indicated. This is done under fluoroscopic control, with catheter tip position further confirmed by pressure measurement at the sites noted. The entire procedure should take less than 7 minutes. If a sample cannot be obtained from a specific site because of ventricular premature beats, that site should be skipped until the rest of the run has been completed.
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The left-right dimension in Latin America

The left-right dimension in Latin America

APPENDIX A few previous exercises can be contrasted with some of the results presented here. Given the differences in methods and scales in which they were developed, we will only compare political party's relative ordinal positions along the left-right dimension. First, the largest sample of party locations available, elaborated on the basis of expert judgments around 1993 by John Huber and Ronald Inglehart (1995) includes, out of 42 countries, four countries in Latin America. The parties shared in their and our analyses from Chile and Me xico coincide completely in their relative ordinal positions. Regarding Argentina, they locate UCR on the left to PJ, but our alternative positions can be explained by UCR's very recent moves, as discussed in the text. Regarding Brazil, we also register an exchange of relative positions between PSDB and PMDB, which may be attributed to the more recent experience of PSDB in government with more- rightist-than-expected policies and management.
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right brain left brain harmony

right brain left brain harmony

Messages attributed to a commercial source have much lower credibility and much lower impact on the perception of product quality than the same message attributed[r]

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Left is right and right is left? Partisan difference on social welfare and particularistic benefits in Japan, South Korea and Taiwan

Left is right and right is left? Partisan difference on social welfare and particularistic benefits in Japan, South Korea and Taiwan

However, policy-orientation is highly path-dependent. As pointed out by Pierson ( 2001 ), policies create politics and four inter-connected aspects of politics – importance of collective action, high density of institutions, possibility of using political authority to perpetuate power asymmetry, and intrinsic com- plexity – make it more conducive to positive feedback. And at the group level, the path-dependent nature becomes even more apparent as ideas are shared by other actors and make particular norms appropriate as collective and self-reinforcing processes. Japan, Korea and Taiwan are no exception to this. Clientelistic norms and related networks right-wing parties developed to capture voters through particularistic benefits during the one-party dominance period would not easily disappear even after the beginning of multi-party competition. For instance, during the one-party dominance period, Japan’s LDP developed a web of institutions to further their electoral advantage, such as the koenkai (vote-mobilization machine), within party-level factions, zoku-gin (policy tribes) and PARC (Policy Affairs Research Council). Noted by Krauss and Pekkanen ( 2010 ), these institutions are complementary in nature and have coevolved over time. Moreover, a dense web of institutions in the political domain have become intertwined with the economic domain at the levels of individuals, firms and organizations (Witt, 2006 ), reinforcing the positive effect of path dependency through denser and more complex institutions. Even after the beginning of multi-party competition and the change of electoral rule in the early 1990s, their utility has not vanished (although it has weakened) and they continue to serve the electoral purpose of right-leaning party members. Indeed, they continue to respond to the expectations of LDP supporters, many of whom are based in rural areas or related to specific industries as vested interests. Although the specific clienteles and the mode of party-vote exchanges vary between presidential Korea and Taiwan and parliamentary Japan (Park, 2008 ; Wang,
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Left right asymmetry in heart development and disease: forming the right loop

Left right asymmetry in heart development and disease: forming the right loop

Left-right asymmetric heart morphogenesis in the mouse The efficient genetic tools available in the mouse model have been essential for dissecting the mechanisms and tracking specific cell populations underlying morphogenesis of the four-chambered heart. In the mouse, cardiac precursors first differentiate at the cardiac crescent stage (E8.5c, Fig. 6A), as recently analysed by time-lapse imaging (Ivanovitch et al., 2017). The right and left heart fields, which initially bulge at E8.5d, fuse to form a heart tube and at E8.5f the right ventricular region lies cranially to the primitive left ventricle (Zaffran et al., 2004). Although the shape of the heart tube looks bilaterally symmetrical from a ventral point of view, a rightward rotation of the arterial pole, by 25°, has been detected from 3D reconstructions of the heart (Le Garrec et al., 2017). This, in addition to the leftward displacement of the venous pole, then results in a rightward tilt of the tube at E8.5 g, which is the first external sign of left-right asymmetry (Biben and Harvey, 1997). Looping progresses, while the tube axis extends by addition of precursor cells at the arterial and venous pole (Domínguez et al., 2012; Kelly et al., 2001) and while the dorsal mesocardium breaks down (Le Garrec et al., 2017). At E8.5j, the heart tube has acquired a helical shape in which the right ventricle has been repositioned on the right of the left ventricle. Between E8.5e and E8.5j (Fig. 6A), heart looping occurs within about 12 h, during which time the length of the tube increases more than fourfold, from 180 to 800 µm (Le Garrec et al., 2017) and from 700 to 3000 cells (de Boer et al., 2012). Concomitant with heart looping, the entire embryo rotates rightward, by 180°, along its antero-posterior axis (see Fujinaga, 1997). This is a process referred to as embryo turning, during which the ventral side of the embryo, initially outside the yolk sac, is internalised and flexed. In experimental conditions, the direction of embryo turning can be uncoupled from that of heart looping (McCarthy and Brown, 1998; Przemeck et al., 2003), suggesting that the two mechanisms operate in parallel. After the completion of heart looping, the tube poles converge along the cranio- caudal axis, such that the outflow tract is positioned above the atria at E10.5. Transgenic markers have illustrated the rotation of the outflow tract from E9.5 (Bajolle et al., 2006), when the heart field is exhausted (Sun et al., 2007), underlying the spiralling of the aorta and pulmonary trunk.
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Left to Right Tree to String Decoding with Prediction

Left to Right Tree to String Decoding with Prediction

The Earley-style decoding algorithm performs a top- down depth-first parsing and generates the target translation left to right. It applies Context-Free Grammar (CFG) rules and employs three actions: predict, scan and complete (Section 3.1 describes how to convert STSG rules into CFG rules). We can simulate its translation process using a stack with a dot indicating which symbol to process next. For the derivation in Figure 1(b) and CFG rules in Fig- ure 1(c), Figure 2 illustrates the whole translation process.

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Left right asymmetry: lessons from Cancún

Left right asymmetry: lessons from Cancún

Magnification of the GRP area shown in B reveals the presence of cilia (black arrowheads). (D) Image of the mouse node, which serves as an LRO and is also ciliated. Cilia are labeled to show localization of the ciliary GTPase Arl13b (red) and acetylated α-tubulin (green). (E) The polycystin protein Pkd1l1 (Pkd1l1-GFP, green) also localizes to cilia (labeled with acetylated α- tubulin; red) in mouse inner medullary collecting duct cells (IMCD-3) and may repress Pkd2 activity. (F) Cross-section of a Xenopus embryo highlighting the extracellular matrix components expressed in the embryo at this stage, with fibronectin (green), laminin (red) and nuclei (DAPI, blue) labeled. The ECM may limit Nodal diffusion in the embryo. (G) In zebrafish, the Nodal ortholog southpaw (arrow) is expressed on the left (L) and induces lefty expression (asterisk) on the left side of the developing heart. (H) In chick, Nodal induces pitx2 expression (blue) on the left side of the dorsal mesentery, which is the tissue that drives leftward midgut rotation. (I) Nodal also directs the zebrafish heart tube (highlighted in blue; cardiac myosin light chain 7, myl7) to ‘jog’ to the left side of the embryo placing the atrium (A) to the left of the ventricle (V). (J-L) Drosophila genitalia rotate clockwise in wild-type embryos. The direction of rotation depends upon myosin 1D activity. Images in A-C are used courtesy of Martin Blum; D is reproduced with permission from Elsevier (Caspary et al., 2007); E is courtesy of Daniel T. Grimes and Dominic Norris; F is courtesy of Chris Wright; G and I are courtesy of Kari Baker Lenhart and Rebecca D. Burdine; H is courtesy of Natasza Kurpios; and J-L are produced courtesy of Suzanne Magali and Stéphane Noselli.
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Left to Right Dependency Parsing with Pointer Networks

Left to Right Dependency Parsing with Pointer Networks

We also take advantage of pointer network cap- abilities and use the neural network architecture introduced by Ma et al. (2018) to design a non- projective left-to-right transition-based algorithm, where the position value pointed by the network has the opposite meaning: it denotes the index that corresponds to the head node of the current focus word. This results in a straightforward trans- ition system that can parse a sentence in just n actions, without the need of any additional data structure and by just attaching each word from the sentence to another word (including the root node). Apart from increasing the parsing speed twofold (while keeping the same quadratic time complexity), it achieves the best accuracy to date among fully-supervised single-model dependency parsers on the PTB-SD, and obtains competitive accuracies on twelve different languages in com- parison to the original top-down version.
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Risk Taking with Left- and Right-Skewed Lotteries

Risk Taking with Left- and Right-Skewed Lotteries

We are only aware of three other studies that investigate how skewness affects risk taking behavior. Grossman and Eckel (2015) use a variation of their Eckel and Grossman (2002, 2008) risk elicitation task and find that when choosing among options with greater skewness, subjects tend to choose riskier options than they did when facing options with lower skewness. In their experiment, subjects choose from six lotteries with the same skewness (and kurtosis) but different expected values or variances. Subjects make (up to) three lottery choices with skewness increasing from zero to two positive levels. However, when controlling for the largest gain in the lottery, their results reverse with subjects taking less risky choices as skewness increases. While Grossman and Eckel (2015) note this is consistent with overweighting the long shot, their experiment is not designed to provide evidence of probability weighting. Astebro, Mata and Santos-Pinto (2015) use a variation of the Holt and Laury (2002) risk elicitation task, modified for different levels of (right) skewness. They find that greater skewness leads to greater risk taking among both students and executives, and with low and high incentives. Using the same choices to estimate average preference parameters for their samples, they rule out risk loving as an explanation but provide support for optimism and likelihood insensitivity. In a different experimental setting using binary lotteries, Ebert (2015) finds that with a symmetric risk, subjects are mostly risk averse but with a right-skewed risk they are mostly risk loving. Thus, similar to these other studies, he finds that risk taking increases with greater skewness.
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Left right patterning: conserved and divergent mechanisms

Left right patterning: conserved and divergent mechanisms

The establishment of left-right (LR) asymmetry during early embryogenesis is crucial for the correct positioning and morphogenesis of internal organs. This process involves a number of intricately regulated developmental mechanisms, some of which appear to be conserved among vertebrates. For some organisms, LR symmetry breaking takes place around the left-right organizer (LR organizer; the node in mice, Hensen’s node in the chick, the gastrocoel roof plate in Xenopus, and Kupffer’s vesicle in zebrafish). In these animals, except for the chick and pig, asymmetric fluid flow produced by rotation of multiple cilia on the LR organizer results in asymmetric gene expression around the LR organizer. Earlier asymmetries in the localization of some molecules are observed in Xenopus and chick embryos and contribute to the establishment of LR asymmetry, but the roles of these molecules in establishing LR asymmetry in other organisms still need to be established (Spéder et al., 2007; Vandenberg and Levin, 2010). Following the symmetry-breaking event, asymmetric information is transmitted to surrounding tissues and induces the asymmetric expression of Nodal and Lefty. Nodal and Lefty,
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Source Side Left to Right or Target Side Left to Right? An Empirical Comparison of Two Phrase Based Decoding Algorithms

Source Side Left to Right or Target Side Left to Right? An Empirical Comparison of Two Phrase Based Decoding Algorithms

Recently, Chang and Collins (2017) proposed a phrase-based decoding algorithm that processes the source-language string in strictly left-to-right order. Reordering is implemented by maintaining multiple sub-strings in the target-language, with phrases being used to extend these sub-strings by various operations (see Section 2 for a full descrip- tion). With a fixed distortion limit on reordering,

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Cilia, calcium and the basis of left-right asymmetry

Cilia, calcium and the basis of left-right asymmetry

A recent study from Hamada and colleagues (Shinohara et al. [37]) utilizes a mixture of genetics, biophysics and imaging to examine the establishment of L­R asymmetry at the node. Th e authors make the striking fi nding that just two rotating cilia are suffi cient to break L­R sym­ metry. In previous studies, nodal fl ow has been examined by following the movement of small numbers of particles across the node, allowing overall direction a lity and speed of fl ow to be assessed. For this study Shinohara et al. used an approach called particle image velocimetry (PIV), which they have customized for nodal­fl ow analysis [38]. Utilizing a high density of fl uorescent beads within a living node and high­speed confocal imaging of a single optical plane, they followed small variations in particle position over many frames, building up a vector map of fl ow and forces across the entire node. At a local level this provides far more information than the particle­tracking approaches used up to now, and it seems likely that PIV Figure 2. Three models of how fl ow breaks symmetry at the node. The node is represented in section, with the axes rotated by 90° from Figure 1; the axes are marked. (a) The morphogen hypothesis posits that a morphogen produced within the node becomes asymmetrically localized between left and right in response to fl ow (represented by the gray gradient). The resulting stronger left-sided signal is detected, thereby breaking symmetry. (b) The nodal vesicular parcel (NVP) hypothesis contends that morphogen-containing vesicles are carried leftwards by nodal fl ow, breaking in contact with cilia on the left side of the node. This delivers the morphogens within the NVPs asymmetrically, resulting in enriched morphogen signaling on the left-hand side of the node, thereby breaking symmetry. (c) The two-cilia hypothesis argues that fl ow itself is detected on the left side of the node by cilia-localized polycystic kidney disease (polycystin or PKD) family molecules, releasing a left-sided Ca 2+
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Left and right brain hemispheres and their effect on creativity

Left and right brain hemispheres and their effect on creativity

Rochester Institute of Technology RIT Scholar Works Theses Thesis/Dissertation Collections 8-1-1976 Left and right brain hemispheres and their effect on creativity Catherine Hraber Follo[r]

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