Sentences with phrase «measured outcome variable»

Only cardiovascular tissues associated with one male pup per litter per measured outcome variable were used to control for sex and within - litter variation.

Using age - and gender - specific z scores for the repeated measures outcome variable and birth weight as the covariate, the between - group variable (breastfeeding medication group) was significant (P =.005).

Not exact matches

This method assumes that the exposures and outcome measures are missing completely at random given the observed variables and the imputed covariates.

Are the outcome measures clearly related to the variables with which the study occurred?

«We're hoping to impress upon the scientific community the notion that for those of us who might be interested in predicting an outcome of interest, possibly with rather complex or high dimensional data, we might gain by reconsidering the question as one of how to search for highly predictive variables (or variable sets) and using statistics that measure predictivity to help us identify those variables to then predict well,» Lo said.

To identify methodological categories, the outcome of each paper was classified according to a set of binary variables: 1 - outcome measured on biological material; 2 - outcome measured on human material; 3 - outcome exclusively behavioural (measures of behaviours and interactions between individuals, which in studies on people included surveys, interviews and social and economic data); 4 - outcome exclusively non-behavioural (physical, chemical and other measurable parameters including weight, height, death, presence / absence, number of individuals, etc...).

However, because of the wide variety of study populations, limitations in some study designs, and variable outcome measures, further research is needed to enhance the ability to generalize and apply yoga to reduce anxiety.

Education is a complex policy area in which outcomes are determined by a host of difficult - to - measure variables, many of which are outside of schools» control.

Pages of Download Grade 2 Practice Sheets: 1 - Cover 2 - For the Teacher 3 - 6 - Measurement Length 7 - 11 - Measurement Height 12 - 15 - Place Value 16 - 20 - Ordinal Numbers 21 - 25 - Smallest / Largest Number in a set of numbers 26 - 29 - Greater than 30 - 33 - Less than 34 - 36 - Greater than / Less than 37 - 39 - Add or subtract write the sign in the blank 40 - 45 - Adding using place value (example: 4 + 13 + 5) 46 - 51 - Adding with words - Example - what is 150 more than 200 52 - 55 - Skip Counting 56 - 59 - Skip Counting - Missing Numbers on a Number line 60 - 65 - Reading Graphs 65 - 71 - Solving Word Problems 72 - 76 - Time 77 - 83 - Coin Identification and Coin counting 84 - 88 - Counting Dollars and coins 89 - 92 - Geometry 93 - 96 - Fractions 97 - 115 - Answer Keys 116 - 118 - Terms of Use and Credits Pages of Download Grade 3 Practice Sheets: 1 - Cover 2 - For the Teacher 3 - 6 - Measurement Length 7 - 11 - Measurement Height 12 - 19 - Place Value 20 - 24 - Find the smallest / largest number from a set of numbers 25 - 28 - Number Words 29 - 32 - Skip Counting - complete the sequence 33 - 37 - Counting dollars and coins 38 - 48 - Reading thermometers - temperature 49 - 53 - Reading graphs 54 - 57 - Reading Calendars 58 - 62 - Numerators and Denominators 63 - 67 - Fraction Circles 68 - 72 - Fractions of a solid 73 - 78 - Word Problems 79 - 83 - Data Tables 84 - 88 - Multi-Step Word Problems 89 - 92 - Rounding to the nearest ten 93 - 96 - Rounding to the nearest hundred 97 - 100 - Rounding word problems 101 - 103 - Probability 104 - 107 - Geometry - identifying shapes 108 - 110 - Height of a triangle 111 - 113 - Angles identifying right, acute, and obtuse 114 - 117 - Symmetry and Angles 118 - 121 - Perimeter 122 - 125 - Area 126 - 129 - Elapsed Time 130 - 155 - Answer Keys 156 - 158 - Credits and Terms of Use Pages of Download Grade 4 practice sheets: 1 - Cover 2 - For the Teacher 3 - 6 - Measurement Length 7 - 11 - Patterns 12 - 15 - Parallel and Perpendicular Lines 16 - 26 - Reading Temperature 27 - 31 - Reading Graphs 32 - 36 - Coordinate Graphs 37 - 41 - Skip Counting - complete the sequence 42 - 46 - Place Value 47 - 50 - Number Words 51 - 55 - Powers of 10 56 - 60 - Adding using Place Value 61 - 70 - Fractions 71 - 75 - Fraction Word Problems 76 - 80 - Convert Fractions to Decimals 81 - 85 - Convert Decimals to Fractions 86 - 90 - Height of a figure 91 - 95 - Missing Number in an equation 96 - 100 - Balancing Equations 101 - 105 - Data Tables - ordering numbers 106 - 110 - Data Table Addition 111 - 115 - Data Table Time 116 - 120 - Data Table Subtraction 121 - 125 - Estimation Word Problems 126 - 130 - Ratio Word Problems 131 - 134 - Probability 135 - 140 - Spinner Probability 141 - 145 - Arrays 146 - 173 - Answer Keys 174 - 177 - Credits and Terms of Use Pages of Download Grade 5 Sheets: 1 - Cover 2 - For the Teacher 3 - 7 - Units of Measure 8 - 12 - Reading Graphs 13 - 17 - Number Words 18 - 22 - Place Value 23 - 27 - Decimal Place Value 28 - 32 - Rounding Numbers 33 - 37 - Complete the sequence, skip counting 38 - 42 - Solving Equations 43 - 47 - Variable Equations 48 - 52 - Simplify Expressions 53 - 57 - Finding the Mean 58 - 62 - Mean, Median, Mode 63 - 67 - Greatest Common Factor 68 - 72 - Fractions 73 - 77 - Comparing a set of Fractions 78 - 83 - Comparing Multiple Fractions 84 - 93 - Fraction Word Problems 94 - 98 - Estimating / Estimation Word Problems 99 - 103 - Possible Outcome Problems 104 - 108 - Distance Word Problems 109 - 113 - Division Word Problems 114 - 118 - Ratio Word Problems 119 - 124 - Coordinate Graphs 125 - 130 - Perimeter 131 - 135 - Area 136 - 145 Elapsed Time Clocks and Watches 146 - 171 - Answer Keys 172 - 175 - Credits and Terms of Use

The Campbell Collaboration's registry contains at least 50 entries on analogous trials in which conventional measures of academic achievement were the main outcome variable.

Our primary outcome variable is student achievement as measured by performance on standardized tests.

Due to the complexity of the study, the fact that many of the classroom variables focus on grades 1 - 3 (e.g., student level of engagement, time spent in small - or whole - group instruction, preferred interaction style), and the use of different outcome measures, the kindergarten classrooms were dropped from the analysis.

For our final analysis, we conducted a stepwise regression in which the most powerful school level (systematic internal assessment and parent links) and classroom level (time in small - group instruction and time in independent reading) variables were simultaneously regressed on our most robust outcome measure, fluency as indexed by words correct per minute on a grade level passage.

To investigate the relationship between school effectiveness and classroom instruction, we initially conducted a multivariate analysis of variance (MANOVA) with the school effectiveness rating serving as the independent variable and eight teacher variables serving as outcome measures (see Table 11).

In a nutshell, she points out that the MET study asked whether actual observation of teaching, student surveys, or VAM test score measures did a better job of predicting future student test score growth, which «privileges» test scores by using it both as a variable being tested and as the outcome reflecting gains.

A Value - Added Model (VAM) is a multivariate (multiple variable) student growth model that attempts to account or statistically control for all potential student, teacher, school, district, and external influences on outcome measures (i.e., growth in student achievement over time).

In the time between screening and outcome measures, instruction, absences, maturation, and other variables occur with variation at individual rates that make predictions very difficult.

CIV is generally prevalent when a test measures too many variables, including extraneous and uncontrolled variables that ultimately impact test outcomes and test - based inferences (Haladyna & Downing, 2004)[and the statistics, no matter how sophisticated they might be, can not control for or factor all of this out].

In the process, they generate data by measuring marble roll distances multiple times, pool their data, and enter it on line plots to better see, understand, and analyze how manipulating the different variables affects the outcomes.

These systems included measures of school context (resources, student background variables, and so on); processes (curriculum coherence, leadership and teaching, and so on); and outcomes (student achievement, graduation rate, school safety, and so on).

Outcome: With regard to variables measured via urinalysis, there were no differences between male and female cats within either group.

Any outcome that can be measured in a lab and used to prove is computable, and any computable outcome can be produced by hidden variables.

So far, only three published studies have analyzed the association between brief readability and case outcome, 50 and no studies have analyzed that association in the trial courts, where most lawyers practice.51 Long and Christensen sampled 882 appellate briefs from the Supreme Court, federal appellate courts, and state supreme courts.52 Their dependent variable was the outcome of the appeal (affirmed or reversed), while their independent variable was readability measured by the Flesch Reading Ease score as calculated by Microsoft Word.53 For federal appellate and state supreme court briefs, the researchers coded control variables for federal or state court, standard of review, presence of a dissenting opinion, and readability of the opinion deciding the appeal.54 For United States Supreme Court briefs, the researchers coded control variables for constitutional issue, criminal or civil case, presence of a dissenting opinion, and opinion readability.55 They found no statistically significant correlation between readability and outcome in the briefs in their study.56

Campbell published the early results of a similar study of petitioners» and appellants» briefs in the Supreme Court, Ninth Circuit, and California Supreme Court.57 He used the StyleWriter writing and editing software package to capture eight different readability measures and coded one dependent variable (the appellant's outcome).58 When considering all appellate briefs, none of the eight readability measures showed a statistically significant correlation to appellant's outcome.

In the first level of analysis, we looked at outcome measures, without controlling for demographic variables.

We also modelled the developmental measures as continuous variables (standardised to facilitate comparisons) and results were again consistent with those obtained using the dichotomised outcomes (tables available on request).

In an additional test of attrition effects, the interaction of intervention condition with attrition was assessed with respect to each outcome variable reported inTable 3 by examining attrition - by - condition interaction effects on corresponding measures at fifth - grade entry.

For the treatment period, the primary analysis for continuous measures was an analysis of variance using the slope of change in the primary variables as the outcome measures and center, treatment, negative affect subtype, and all interactions as the independent measures.

First, for females there was very little variation in the dependent variables, with less than one percent of the sample of females scoring two standard deviations above the mean on the outcome measures.

Missing values were predicted using an iterative series of appropriate regression models (logistic or multinomial) conditional on the observed values of the outcome variable, independent variables used in regression modelling and additional measured variables.

A palpable relationship exists between ACE scores and independent variables measuring clinical impairment and outcomes.

Only variables significantly related to TV - viewing time were considered to potentially confound the relationship between this outcome measure and either maternal depression or maternal obesity.

It has been shown that inferences resulting from this analysis are virtually identical no matter which of these outcome measures is used.30 In addition to the covariates previously noted, the regression analysis was repeated to include annual household income, mother's treatment setting (primary vs psychiatric outpatient care), and treatment status of child during the 3 - month follow - up period in order to investigate the further potential confounding effects of these variables.

Importantly, family type is not significantly associated with health outcome measures when other key variables are considered.

Large data material consisting of both adolescent and parental health variables combined with almost complete information on outcome measures from National registers.

(i) For each of the outcome variables, a linear regression was performed for each student group, which provides measures of the linear trends as effects of the intervention.

First, multilevel modelling was used to estimate the impact of CfC by comparing the difference between CfC and comparison sites in the outcome measures at wave 3 after taking account of demographic variables (see table 2).

One method is to measure a number of variables that could possibly influence A and B groups differently and «subtract them» from the outcome to see if any effect of the intervention remains.

We found no associations between child involvement and other treatment variables, however, it is not entirely clear what role child and parent involvement played and it would be useful for studies to look at the relative merits of child alone vs. family - wide involvement in the FDP as a measure of treatment outcome and process.

Summary: (To include comparison groups, outcomes, measures, notable limitations) The aim of this study was to conduct a evaluation of the effectiveness of Circle of Security - Parenting (COS - P), with mothers in residential substance abuse treatment and (b) to examine what demographic variables, including other risk factors for child maltreatment, may influence the impact of the program with these mothers.

The outcomes were measured with composite variables computed as a mean of at least two scales.

This outcome study was designed as a quantitative study that took place over 3 - time intervals and measured change in intimacy based on 3 variables (satisfaction, conflict resolution, and communication) as perceived by individuals from an RLT Couple Experiential Treatment group and a Control group.

Because of these variables, the field needs a way to measure outcomes across each state's portfolio of programs.

The dependent variable for each model is the relevant driver of child outcomes named in the column headings, the separation event and the sweep 1 measure of the driver are listed down the left and the arrows indicate the direction of any significant association.

Multiple regression analyses were used to assess the relation between the same independent predictor variables and dimensional outcome measures (Karnofsky performance index).

The relations between independent predictor variables (measures of immunological and psychological function at entry to the trial, age of onset, and duration of illness) and dependent dichotomous outcome variables (self rated global outcome; presence or absence of caseness on the general health questionnaire at follow up; reduced or normal delayed responses to hypersensitivity skin test) were examined in separate logistic regression analyses.

Because of the large number of comparisons (each predictor variable for three outcome measures), results were only considered significant at the p <.01.

In contrast, moderators are variables that can be measured before treatment and are associated with treatment outcome, but the magnitude or direction of the effect differs across treatments (e.g., if boys did better in behavior therapy and girls in interpersonal therapy, then gender is a moderator).

In addition, 53 % of the usual care - group subjects received «usual care» but without any measurable change in the outcome variables measured.

In doing so, it summarizes methods of measuring EE, the nature of professional EE compared with familial EE, associations between high EE and patient outcomes, associations between EE and both patient and staff variables, and intervention studies to reduce staff high EE.