the 30-item inventory of depressive symptomatology ( ids30 ) ( rush et al 1996 , 2000 ; trivedi et al 2004b ) has been widely used and evaluated using classical test theory methods . the standard total score is obtained by summing the ratings of 28 of the 30 items . either weight loss or weight gain , appetite loss or appetite gain is scored because only one member of each pair is applicable to any given respondent . each of the 28 items is scored on a 0 to 3 scale ( 0the absence of pathology ; 3severe pathology ) . standard scoring assumes a traditional model of tests known as classical test theory ( ctt ) in which the trait score ( depression in this case ) represents the scale score total plus random error of measurement . items are the unit of analysis . totaling individual items is not the only way to score a test . for example , the 16-item quick inventory of depressive symptomatology ( qids16 ) ( rush et al 2000 , 2003b ; trivedi et al 2004b ) uses domain scoring such that when more than one item belongs to the same general domain ( eg , four items assess sleep disturbance ) , the items are grouped and assigned a single score for that domain based upon the highest ( most pathological ) score for the domain - related items . thus , for the qids , the scores for three domains are based on more than one item ( 4 items for sleep disturbance , 2 items for psychomotor disturbance , and 4 items for the appetite / weight domain ) . each of the remaining 5 items is individually scored for each domain ( eg , sad mood , concentration , decision making ) . this method allows the use of ctt analyses with the nine domains rather than items as the units of analysis . the total score ranges from 0 to 27 rather than the 0 to 48 which would have been the case had each of 16 items been scored individually and totaled . item response theory ( irt ) methods ( in particular the samejima model ) ( samejima 1997 ) is particularly suited for graded item responses ( eg , 03 ratings on items or domains ) as with the ids and qids . all irt models scale individual items in terms of their location on an inferred continuum using a complex mathematical procedure . the underlying continuum , denoted as    , refers to depression severity in this report . one can employ either the ctt or irt approach to evaluate items or domains assessed by scales like the ids or qids . the level of response ( or severity of pathology ) is the item mean ( x ) . the relation of the item to overall depression is the item / total correlation ( rit ) . the larger the value of the individual item or domain , x the more severe the symptom . the higher the value of rit , the more closely the rated symptom relates to overall depression . the item ( or domain ) mean ( x ) and the item ( domain ) total correlation ( rit ) may not be strongly related to each other . for example , sleep disturbance items on both the ids and qids generally have among the highest values of x , but these sleep disturbance items are only modestly related to overall depression severity as judged by the total scale score ( ie , their rit values are not particularly large ) . conversely , sad mood may have a lower x value , but it is more highly related to overall depression than sleep disturbance , which is expected since sad mood is a core depressive symptom ( apa 2000 ; bernstein et al 2006 ) . irt allows one to formally equate scores on different scales so that a total score , say x , on one depression scale can be shown equivalent to a score of y on another . for example , we recently used irt ( carmody et al 2006b ) to equate total scores on the qids and the montgomery - sberg depression rating scale ( madrs ) ( montgomery and sberg 1979 ) . we did the same ( carmody et al 2006a ) with the madrs and the 17-item hamilton rating scale for depression ( hamilton 1960 , 1967 ) . secondly , irt allows for a comparison of groups defined , for example , by gender or other baseline demographic or clinical features in terms of both individual item responses and the frequency of different item responses in relation to overall depression severity . ctt also easily allows tests of differences in x , but with ctt testing difference in rit is somewhat complex ( see rush et al 2006 ) . when specific items perform differently in different respondent groups , the term differential item functioning ( dif ) is used . finally , irt ensures a more linear relationship between the construct of depression and individual items than does the ctt approach , which might lead the resulting scores to have more optimal properties . on the other hand , ctt methods always produce results even if the scale has undesirable properties such as low internal consistency . the irt analyses may not be feasible in some cases because irt analyses require stronger assumptions . for example , most irt models assume an s - shaped relation between the magnitude of the trait and the item response . ctt analyses have been conducted with the ids ( rush et al 1996 ) , but irt analyses have not been reported . the sample was obtained from the texas medication algorithm project ( tmap ) ( rush et al 2003a ; trivedi et al 2004a ) , which was conducted in accordance with international guidelines for good clinical practice and the declaration of helsinki . tmap was approved by the institutional review boards at the university of texas southwestern medical center and the university of texas , austin , as well as by each local institutional review board where applicable . adult outpatients with major depressive disorder ( mdd ) were recruited from the public sector ( bernstein et al 2006 ; trivedi et al 2004a , 2004b ) . the original sample of 547 out - patients with mdd was reduced to 428 by excluding those with mdd with psychotic features . both the self - report ( ids - sr30 ) and clinician - rated ( ids - c30 ) versions of the 30-item inventory of depressive symptomatology ( rush et al 1996 , 2000 ; trivedi et al 2004b ) were obtained at exit by a research coordinator not involved in patient treatment . the goal of the analyses was to jointly fit the samejima irt model to the ids - sr30 and the ids - c30 and to evaluate differences between these two scales . we compared the successive eigenvalues ( scree ) to those obtained by randomly generated correlations using the same number of variables and observations in a procedure known as parallel analysis ( horn 1965 ; humphreys and ilgen 1969 ; humphreys and montanelli 1975 ; montanelli and humphreys 1976 ) . the number of components ( dimensionality ) is the number of components in the real data for which eigenvalues exceed those that were randomly generated . since each item on each scale has four response alternatives ( ratings on a 03 scale ) , the samejima model generated 4 parameters per item . one parameter describes how strongly each of 3 functions relates item ( or domain ) responses ( ie , symptoms ) to overall depression . these three functions respectively denote : ( a ) the tendency for a symptom to be reported as a  1  ,  2  or 3  relative to a  0  , ( b ) the tendency for a symptom to be reported as a  2  or a  3  relative to a  0  or  1  , and ( c ) the tendency for a symptom to be reported as a  3  relative to a  0  ,  1  , or  2  . the locations of the respective functions are symbolized b0 , b1 , and b2 ( collectively bi ) . these locations denote the relative frequency of the dichotomized responses . a scale with mean of 0 and standard deviation 1 is common . thus , if the estimate of b0 ; to equal 0 , it would imply that a  0  response is made half the time and a  1  ,  2  , or 3  is made the remainder of the time . the slope is symbolized  a  , which corresponds to the item / total correlation of ctt in measuring how strongly a given symptom domain relates to overall depression severity . to illustrate how the irt approach works , consider our previous work with the qids - sr16 and qids - c16 , each of which scores 9 domains ( the criterion symptoms to diagnose a major depressive episode ) ( bernstein et al 2006 ; rush et al 2006 ) . a base model was constructed pooling the two scales into a single 18-domain scale using exit data from the tmap database ( trivedi et al 2004b ) . the four parameters ( a , b0 , b1 , b2 ) from a given item on the qids - sr16 were allowed to take on different values from the four parameters of the corresponding item on the qids - c16 , resulting in 72 free parameters ( 2 scales  9 domains  4 parameters / domain ) . the individual a parameters were then tested individually by constraining each , one at a time , to be the same value in the two scales . the difference between the two fits is approximately distributed as a form of chi - square known as the likelihood - ratio chi - square ( g ) and was tested for significance with 1 df , representing the one parameter that was constrained . a significant value implies that the item slope ( a ) differed across the two scales . next , the a parameters were allowed to vary freely , but the three b parameters / item within each domain were constrained to equality . values of g were again obtained by comparing the value obtained from the constrained version to the value obtained from the base model . each of these nine tests was based upon 3 df , representing the three intercepts that were constrained for each domain . a significant result implies that there are intercept differences between the two scales involving that domain . that would have meant that symptoms in that domain are reported with different frequencies by the qids - c16 and the qids - sr16 . in fact , no significant slope differences were found , and only one intercept difference was found ( for agitation / retardation ) . when slopes or intercept differences are found between groups or measurement methods ( in this case ) , the term differential item functioning ( dif ) is used . in the case of the qids , only the agitation / retardation domain performed differently when one scale as opposed to another was used . even then , the difference was not in the degree of relationship between the symptom and overall depression ( ie , the a parameter was not different ) . an anomalous result means that a better fit is found with a more constrained than a less constrained model , which leads to a spurious  negative g. such a result can arise from various sources : ( a ) very high correlations between individual items , ( b ) small cell frequencies , or ( c ) long scales . when we conducted similar analyses with the 30-item ids scales , such anomalies were encountered . consequently , we made the following modifications to successfully fit the model and to test for dif : ( a ) we replaced scoring of individual items with domain scores for sleep , psychomotor , and appetite / weight domains ; ( b ) we pooled items with few positive responses ; and ( c ) we changed how the base model was tested . specifically , ids items 14 were combined into a single sleep domain ; items 1114 were combined into a single appetite / weight domain , and items 2324 were combined into a single psychomotor domain ( analogous to the standard scoring of the qids16 ) ( rush et al 2003b ) . next , items 68 , 16 , and 21 ( diurnal mood variation , distinct quality to mood , distinct mood quality , interest in sex , and gastrointestinal complaints ) were dichotomized into 0 vs 1 or greater because responses of 2 or greater to each of these items were rare . finally , the tested strategy was reversed by first generating a base model in which all parameters were constrained to equality and then freeing a parameters individually and bi parameters in groups of 3 . this procedure ( the converse of what was used with the qids16 ) maintains the idea of comparing more vs. less constrained models . as an addendum to this testing , individual bi parameters were tested specifically by freeing them whenever the entire group of three parameters differed . for example , if there was a difference in the overall distributions of the sad mood response frequencies between the two rating scales , more specific differences involving the three specific dichotomies ( 0 vs 1 to 3 , 0 or 1 vs 2 or 3 , and 0 to 2 vs 3 ) were examined individually . finally , the test information functions of the ids and the qids ( obtained by extracting the relevant items from the ids were compared . in the present context , the test information function ( tif ) describes how well a test can discriminate small differences in depression as a function of the score  the higher the value , the more discriminating the test . tif bears similarities to the internal consistency ( coefficient alpha ) obtained by ctt , but the tif reveals how test information varies over different levels of depression rather than being computed as a constant . the sample was obtained from the texas medication algorithm project ( tmap ) ( rush et al 2003a ; trivedi et al 2004a ) , which was conducted in accordance with international guidelines for good clinical practice and the declaration of helsinki . tmap was approved by the institutional review boards at the university of texas southwestern medical center and the university of texas , austin , as well as by each local institutional review board where applicable . adult outpatients with major depressive disorder ( mdd ) were recruited from the public sector ( bernstein et al 2006 ; trivedi et al 2004a , 2004b ) . the original sample of 547 out - patients with mdd was reduced to 428 by excluding those with mdd with psychotic features . both the self - report ( ids - sr30 ) and clinician - rated ( ids - c30 ) versions of the 30-item inventory of depressive symptomatology ( rush et al 1996 , 2000 ; trivedi et al 2004b ) were obtained at exit by a research coordinator not involved in patient treatment . the goal of the analyses was to jointly fit the samejima irt model to the ids - sr30 and the ids - c30 and to evaluate differences between these two scales . we compared the successive eigenvalues ( scree ) to those obtained by randomly generated correlations using the same number of variables and observations in a procedure known as parallel analysis ( horn 1965 ; humphreys and ilgen 1969 ; humphreys and montanelli 1975 ; montanelli and humphreys 1976 ) . the number of components ( dimensionality ) is the number of components in the real data for which eigenvalues exceed those that were randomly generated . since each item on each scale has four response alternatives ( ratings on a 03 scale ) , the samejima model generated 4 parameters per item . one parameter describes how strongly each of 3 functions relates item ( or domain ) responses ( ie , symptoms ) to overall depression . these three functions respectively denote : ( a ) the tendency for a symptom to be reported as a  1  ,  2  or 3  relative to a  0  , ( b ) the tendency for a symptom to be reported as a  2  or a  3  relative to a  0  or 1  , and ( c ) the tendency for a symptom to be reported as a  3  relative to a  0  ,  1  , or  2  . the locations of the respective functions are symbolized b0 , b1 , and b2 ( collectively bi ) . these locations denote the relative frequency of the dichotomized responses . a scale with mean of 0 and standard deviation 1 is common . thus , if the estimate of b0 ; to equal 0 , it would imply that a  0  response is made half the time and a  1  ,  2  , or  3  is made the remainder of the time . the slope is symbolized  a  , which corresponds to the item / total correlation of ctt in measuring how strongly a given symptom domain relates to overall depression severity . to illustrate how the irt approach works , consider our previous work with the qids - sr16 and qids - c16 , each of which scores 9 domains ( the criterion symptoms to diagnose a major depressive episode ) ( bernstein et al 2006 ; rush et al 2006 ) . a base model was constructed pooling the two scales into a single 18-domain scale using exit data from the tmap database ( trivedi et al 2004b ) . the four parameters ( a , b0 , b1 , b2 ) from a given item on the qids - sr16 were allowed to take on different values from the four parameters of the corresponding item on the qids - c16 , resulting in 72 free parameters ( 2 scales  9 domains  4 parameters / domain ) . the individual a parameters were then tested individually by constraining each , one at a time , to be the same value in the two scales . the difference between the two fits is approximately distributed as a form of chi - square known as the likelihood - ratio chi - square ( g ) and was tested for significance with 1 df , representing the one parameter that was constrained . a significant value implies that the item slope ( a ) differed across the two scales . next , the a parameters were allowed to vary freely , but the three b parameters / item within each domain were constrained to equality . values of g were again obtained by comparing the value obtained from the constrained version to the value obtained from the base model . each of these nine tests was based upon 3 df , representing the three intercepts that were constrained for each domain . a significant result implies that there are intercept differences between the two scales involving that domain . that would have meant that symptoms in that domain are reported with different frequencies by the qids - c16 and the qids - sr16 . in fact , no significant slope differences were found , and only one intercept difference was found ( for agitation / retardation ) . when slopes or intercept differences are found between groups or measurement methods ( in this case ) , the term differential item functioning ( dif ) is used . in the case of the qids , only the agitation / retardation domain performed differently when one scale as opposed to another was used . even then , the difference was not in the degree of relationship between the symptom and overall depression ( ie , the a parameter was not different ) . an anomalous result means that a better fit is found with a more constrained than a less constrained model , which leads to a spurious  negative g. such a result can arise from various sources : ( a ) very high correlations between individual items , ( b ) small cell frequencies , or ( c ) long scales . when we conducted similar analyses with the 30-item ids scales , such anomalies were encountered . consequently , we made the following modifications to successfully fit the model and to test for dif : ( a ) we replaced scoring of individual items with domain scores for sleep , psychomotor , and appetite / weight domains ; ( b ) we pooled items with few positive responses ; and ( c ) we changed how the base model was tested . specifically , ids items 14 were combined into a single sleep domain ; items 1114 were combined into a single appetite / weight domain , and items 2324 were combined into a single psychomotor domain ( analogous to the standard scoring of the qids16 ) ( rush et al 2003b ) . next , items 68 , 16 , and 21 ( diurnal mood variation , distinct quality to mood , distinct mood quality , interest in sex , and gastrointestinal complaints ) were dichotomized into 0 vs 1 or greater because responses of 2 or greater to each of these items were rare . finally , the tested strategy was reversed by first generating a base model in which all parameters were constrained to equality and then freeing a parameters individually and bi parameters in groups of 3 . this procedure ( the converse of what was used with the qids16 ) maintains the idea of comparing more vs. less constrained models . as an addendum to this testing , individual bi parameters were tested specifically by freeing them whenever the entire group of three parameters differed . for example , if there was a difference in the overall distributions of the sad mood response frequencies between the two rating scales , more specific differences involving the three specific dichotomies ( 0 vs 1 to 3 , 0 or 1 vs 2 or 3 , and 0 to 2 vs 3 ) were examined individually . finally , the test information functions of the ids and the qids ( obtained by extracting the relevant items from the ids were compared . in the present context , the test information function ( tif ) describes how well a test can discriminate small differences in depression as a function of the score  the higher the value , the more discriminating the test . tif bears similarities to the internal consistency ( coefficient alpha ) obtained by ctt , but the tif reveals how test information varies over different levels of depression rather than being computed as a constant . figure 2 contains the successive eigenvalues of the ids - c30 and ids - sr30 ( scree ) and those randomly generated . note that both scales meet the criteria for two factors since the first two eigenvalues exceed the randomly generated data . the disparity between the real and randomly generated second eigenvalue , however , was modest . the presence of two factors imposes a limitation on the irt solution to be provided , since that solution assumes unidimensionality . to the extent that depression is represented by the first principal component , the items related to the second principal component define something other than depression that is contributing to the score . table 1 contains the first and second principal component loadings for the ids - sr30 and ids - c30 , respectively . using an arbitrary cutoff of 0.4 to denote a large weight on a given component , the second principal component of the ids - sr30 is defined by aches and pains ( domain 18 ) , symptoms of sympathetic nervous system arousal ( domain 19 ) , and gastrointestinal complaints ( domain 21 ) . these same three items plus the presence of the capacity for pleasure ( negative loading ) ( domain 15 ) formed the second principal component for the ids - c30 . thus , the three items common to both forms deal with somatic symptoms that may not necessarily reflect depression per se , especially in this sample of socially disadvantaged individuals with high rates of general medical conditions ( trivedi et al 2004a ) . scores on the first and second components were then generated for the ids - sr30 and ids - c30 . as expected , the correlation between the first component scores for the ids - sr30 and ids - c30 was extremely high ( r=0.92 ) because both represent the dominant depression component of both scales . the correlation between the two second component scores was also moderately high ( r=0.73 ) . the remaining correlations ( eg , between the first component of the ids - sr30 and the second component of the ids - c30 ) were 0.11 or less , which establishes the independence between the first and second components of each scale . these findings indicate that the multidimensionality within the ids - c30 and ids - sr30 is consistent . table 2 shows the samejima a and bi parameter estimates for the ids - sr30 and ids - c30 when they were each scored to create 23 domains . the last column ( diff . ) identifies domains for which there is a significant difference between the clinician and self - report ratings in the a or bi parameter estimates ( ie , differential item functioning ) ( dif ) . note that three of these are also qids items ( concentration / decision making , capacity for pleasure , restlessness / agitation ) vs one that is peculiar to the ids ( diurnal variation ) . none of the former provided any evidence of a slope difference when scored as part of the qids . therefore , it is not the item itself but rather the broader definition of depression used by the ids that accounts for these differences . each version of the 23 domain - scored ids may be scored two ways  by ctt simply as the as the sum of the 23 domains or by a fairly complex irt algorithm . the correlation between the ctt and irt scores on each of the two scales is high ( 0.92 for ctt and 0.91 for irt ) . the correlation between the two methods of scoring is even higher , 0.97 , for both versions of the scale . however , the ctt and irt methods of scoring the 23 domain - scored versions of the ids - sr30 and ids - c30 reveal that total scores using the two scoring methods are not linearly related . figure 3 shows a scatter plot of the two sets of ids - c30 scores , with irt - generated scores along the abscissa and ctt - generated score along the ordinates . according to irt , the irt - generated scores are , by definition , linearly related to depression (  ) . consequently , the ctt - generated scores are an ogival ( s - shaped ) function of depression . if one accepts the irt scoring of  true  depression , then scores at the high and low ends of the ctt scale represent less difference in depression than scores in the middle . scores in the middle of both scales are linearly related to one another . in other words , very low scores as defined by ctt tend to somewhat underestimate depression , as seen in the minimal changes in such scores following changes in irt - generated scores . similarly , very high scores defined by ctt tend to overestimate depression . however , this effect is modest and may or may not be of clinical significance . the next step was to compare the results of standard 28-item ctt scoring to the two alternative 23 domain scoring methods ( ctt and irt ) . thus , the two ctt methods correlated to nearly identical degrees with the irt scoring . of course , correlations between the 28-item ctt scoring with irt scoring were the same as the correlations between the 23-domain ctt scoring and irt scoring ( 0.97 ) . thus , despite the curvilinearity of ctt scoring , the major properties of both ctt and irt scoring , such as the rank - ordering of individuals , were preserved . finally , test information functions ( tifs ) were generated for the ids and the qids for the 23 domain scored versions of both the self - report and clinical irt versions . these functions describe to what degree change in the level of depression is reflected in changes in irt - defined test scores . the formula for the test information function may be found in nunnally and bernstein ( nunnally and bernstein 1994 , p 408 ) and lord ( lord 1980 , p 68 ) . the tif serves a role that is similar to the internal consistency ( coefficient alpha ) of ctt , but it is a function of the trait being investigated rather than a constant for the test as a whole . thus , the ids - c30 and ids - sr30 relate similarly to overall depression when scored using the 23-domain method . as can be seen , the test information of the ids is approximately twice that of the qids at each level of depression ( generically symbolized    in the language of irt ) . this means that the ids provides a more sensitive measure of depression than the qids . technically , this applies to the irt - scored ( 23 domain ) version of the ids , but the similarities between this scoring and the 28 item scoring plus the clinical and self - report versions make this a rather general conclusion . this result is expected given the greater length and greater breadth of symptom coverage with the ids . also , note that both tests are maximally sensitive with patients who are of average depression to one standard deviation above average in this sample , which means that it is less useful in discriminating among patients low in depression ( remitted depressives and normals ) and those who are extremely depressed . these results may reflect , in part , that relatively few depressives were remitted in this sample . figure 2 contains the successive eigenvalues of the ids - c30 and ids - sr30 ( scree ) and those randomly generated . note that both scales meet the criteria for two factors since the first two eigenvalues exceed the randomly generated data . the disparity between the real and randomly generated second eigenvalue , however , was modest . the presence of two factors imposes a limitation on the irt solution to be provided , since that solution assumes unidimensionality . to the extent that depression is represented by the first principal component , the items related to the second principal component define something other than depression that is contributing to the score . table 1 contains the first and second principal component loadings for the ids - sr30 and ids - c30 , respectively . using an arbitrary cutoff of 0.4 to denote a large weight on a given component , the second principal component of the ids - sr30 is defined by aches and pains ( domain 18 ) , symptoms of sympathetic nervous system arousal ( domain 19 ) , and gastrointestinal complaints ( domain 21 ) . these same three items plus the presence of the capacity for pleasure ( negative loading ) ( domain 15 ) formed the second principal component for the ids - c30 . thus , the three items common to both forms deal with somatic symptoms that may not necessarily reflect depression per se , especially in this sample of socially disadvantaged individuals with high rates of general medical conditions ( trivedi et al 2004a ) . scores on the first and second components were then generated for the ids - sr30 and ids - c30 . as expected , the correlation between the first component scores for the ids - sr30 and ids - c30 was extremely high ( r=0.92 ) because both represent the dominant depression component of both scales . the correlation between the two second component scores was also moderately high ( r=0.73 ) . the remaining correlations ( eg , between the first component of the ids - sr30 and the second component of the ids - c30 ) were 0.11 or less , which establishes the independence between the first and second components of each scale . these findings indicate that the multidimensionality within the ids - c30 and ids - sr30 is consistent . table 2 shows the samejima a and bi parameter estimates for the ids - sr30 and ids - c30 when they were each scored to create 23 domains . the last column ( diff . ) identifies domains for which there is a significant difference between the clinician and self - report ratings in the a or bi parameter estimates ( ie , differential item functioning ) ( dif ) . note that three of these are also qids items ( concentration / decision making , capacity for pleasure , restlessness / agitation ) vs one that is peculiar to the ids ( diurnal variation ) . none of the former provided any evidence of a slope difference when scored as part of the qids . therefore , it is not the item itself but rather the broader definition of depression used by the ids that accounts for these differences . each version of the 23 domain - scored ids may be scored two ways  by ctt simply as the as the sum of the 23 domains or by a fairly complex irt algorithm . the correlation between the ctt and irt scores on each of the two scales is high ( 0.92 for ctt and 0.91 for irt ) . the correlation between the two methods of scoring is even higher , 0.97 , for both versions of the scale . however , the ctt and irt methods of scoring the 23 domain - scored versions of the ids - sr30 and ids - c30 reveal that total scores using the two scoring methods are not linearly related . figure 3 shows a scatter plot of the two sets of ids - c30 scores , with irt - generated scores along the abscissa and ctt - generated score along the ordinates . according to irt , the irt - generated scores are , by definition , linearly related to depression (  ) . consequently , the ctt - generated scores are an ogival ( s - shaped ) function of depression . if one accepts the irt scoring of  true  depression , then scores at the high and low ends of the ctt scale represent less difference in depression than scores in the middle . scores in the middle of both scales are linearly related to one another . in other words , very low scores as defined by ctt tend to somewhat underestimate depression , as seen in the minimal changes in such scores following changes in irt - generated scores . similarly , very high scores defined by ctt tend to overestimate depression . however , this effect is modest and may or may not be of clinical significance . the next step was to compare the results of standard 28-item ctt scoring to the two alternative 23 domain scoring methods ( ctt and irt ) . thus , the two ctt methods correlated to nearly identical degrees with the irt scoring . of course , correlations between the 28-item ctt scoring with irt scoring were the same as the correlations between the 23-domain ctt scoring and irt scoring ( 0.97 ) . thus , despite the curvilinearity of ctt scoring , the major properties of both ctt and irt scoring , such as the rank - ordering of individuals , were preserved . finally , test information functions ( tifs ) were generated for the ids and the qids for the 23 domain scored versions of both the self - report and clinical irt versions . these functions describe to what degree change in the level of depression is reflected in changes in irt - defined test scores . the formula for the test information function may be found in nunnally and bernstein ( nunnally and bernstein 1994 , p 408 ) and lord ( lord 1980 , p 68 ) . the tif serves a role that is similar to the internal consistency ( coefficient alpha ) of ctt , but it is a function of the trait being investigated rather than a constant for the test as a whole . thus , the ids - c30 and ids - sr30 relate similarly to overall depression when scored using the 23-domain method . as can be seen , the test information of the ids is approximately twice that of the qids at each level of depression ( generically symbolized    in the language of irt ) . this means that the ids provides a more sensitive measure of depression than the qids . technically , this applies to the irt - scored ( 23 domain ) version of the ids , but the similarities between this scoring and the 28 item scoring plus the clinical and self - report versions make this a rather general conclusion . this result is expected given the greater length and greater breadth of symptom coverage with the ids . also , note that both tests are maximally sensitive with patients who are of average depression to one standard deviation above average in this sample , which means that it is less useful in discriminating among patients low in depression ( remitted depressives and normals ) and those who are extremely depressed . these results may reflect , in part , that relatively few depressives were remitted in this sample . the samejima model was applied to the clinician and self - rated versions of the ids . as noted above whereas classical methods allow the frequency of symptoms to be compared with ease , classical methods are less suitable to evaluate differences in the relation of symptoms to depression ( or any other trait ) . however , with the ids there was greater difficulty and more strain on the assumption of unidimensionality than was the case with the qids , which , as our earlier papers have shown , was clearly unidimensional ( bernstein et al 2006 ; rush et al 2006 ) . these data suggest that scoring the ids conventionally is satisfactory for making judgments about patient care . conventional scoring ( ie , totaling the 28 items ) allows one to take advantage of the far simpler ctt scoring . it would appear that creating 23 domains offers little advantage because of the relatively large number of items . on the other hand , an irt model generated using the 23-domain scoring method , is important for virtually any research involving the ids , since it means that groups and/or conditions can be compared using the relatively straightforward methods based upon testing for fit differences . this is a major advantage in looking for differences in the relation of domains to depression as a whole . for example , when comparing patients with postpartum depression and depression outside the postpartum period , the revised ids scoring ( 23 domains ) is preferred . at the same time , the fact that ctt and irt scoring lead one to comparable results means that conventional scoring of the ids is appropriate . it is reasonable to ask if the revised ( 23 domain ) scoring in either ctt or irt form is sufficient . the answer is that it is . at the same time , this revised scoring does not seem to be more sensitive to mild depression . one could also ask about jettisoning those items that seem to induce multidimensionality ( ie , gastrointestinal symptoms , somatic complaints , sympathetic arousal ) . however , the loss in comparability with previous studies would probably be greater than any largely theoretical gain . finally , there is the question of whether it is good for many of the items that load on the first principal component to reflect anxiety . that question seems very difficult to answer without considering whether anxiety is or is not an inherent part of depression or whether a large sample of depressed patients could have included some with  anxious depression  and others with minimally or non - anxious depression . limitations in the assertions that an irt model can be created for the ids30 and that it is consistent across methods needs be noted . first , there is a slight , but consistent , degree of multidimensionality in the ids30 that is counter to the assumption of unidimensionality made in standard usage of the samejima model . the precise nature of the second dimension might be different in a sample with less medical comorbidity . standard scoring of the ids - c30 and ids - sr30 provides simplicity and comparability to published data . the present results based on the irt model enhance the validity of comparisons between groups or conditions . while clinical decisions can be made about patients with standard scoring ( ie , totaling all items to obtain a scale score ) , researchers may wish to use this revised irt scoring method to improve the use of the ids when comparing groups . limitations in the assertions that an irt model can be created for the ids30 and that it is consistent across methods needs be noted . first , there is a slight , but consistent , degree of multidimensionality in the ids30 that is counter to the assumption of unidimensionality made in standard usage of the samejima model . the precise nature of the second dimension might be different in a sample with less medical comorbidity . standard scoring of the ids - c30 and ids - sr30 provides simplicity and comparability to published data . the present results based on the irt model enhance the validity of comparisons between groups or conditions . while clinical decisions can be made about patients with standard scoring ( ie , totaling all items to obtain a scale score ) , researchers may wish to use this revised irt scoring method to improve the use of the ids when comparing groups .